Relevant bibliographies by topics / Modelo t de Student

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Modelo t de Student'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Modelo t de Student.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Modelo t de Student"

1

Thomaz, Paulo Siga, Viviane Leite Dias de Mattos, Luiz Ricardo Nakamura, Andréa Cristina Konrath, and Gérson Dos Santos Nunes. "Modelos GARCH em ações financeiras: um estudo de caso." Exacta 18, no. 3 (July 10, 2020): 626–48. http://dx.doi.org/10.5585/exactaep.v18n3.10921.

Full text
Abstract:
Este artigo tem por objetivo detalhar o protocolo de aplicação e avaliação dos modelos autorregressivos de heteroscedasticidade condicional generalizados (GARCH), com ênfase em especificar adequadamente a distribuição de probabilidade para os resíduos e o critério de avaliação da previsão. Com este intuito, aplicam-se modelos GARCH com distribuição normal e t de Student na modelagem da volatilidade da série de retornos das ações ABEV3. O melhor modelo seguindo a distribuição normal e o melhor seguindo a distribuição t de Student são executados para a previsão, em que os resultados são comparados com a volatilidade realizada, calculada a partir de retornos intradiários, e com os retornos absolutos. Os resultados evidenciam que o modelo GARCH(1,1) seguindo a distribuição t de Student possui a melhor performance, tanto no ajuste como na previsão. Além disso, os modelos possuem resultados significativamente melhores quando avaliados pelo critério da volatilidade realizada.
APA, Harvard, Vancouver, ISO, and other styles
2

Hernández García, Melva. "Cultura organizacional y habilidades gerenciales de los directores y profesores, en una asociación educativa." Paidagogo 2, no. 1 (June 6, 2020): 3–25. http://dx.doi.org/10.52936/p.v2i1.22.

Full text
Abstract:
El objetivo de esta investigación es determinar en qué medida la cultura organizacional se relaciona con las habilidades gerenciales, en un enfoque cuantitativo, no experimental, tipos: descriptivo, correlacional y transeccional. En el primer modelo, las dimensiones predictoras “modos de vida” y “conocimiento” influyen positivamente en la dimensión “habilidades técnicas”, pues sus t de Student respectivamente: t= 3.162 y t= 2,652 tiene p-valores 0.003 y 0,011, inferiores a 0.05. En el segundo modelo, las dimensiones predictoras “práctica de valores”, “modos de vida” y “conocimiento” influyen positivamente en la dimensión “habilidades humanas”, pues sus t de Student respectivamente: t= 2.872, t = 3.158 y t= 3.034, con sus p-valores 0.006, 0.003 y 0,004, inferiores a 0.05. En el tercer modelo, las dimensiones predictoras “conocimiento”, “modos de vida” y “práctica de valores” influyen positivamente en la dimensión “habilidades conceptuales”, pues sus t de Student respectivamente: t= 3.662, t = 2.789 y t= 2,250, con p-valores 0.001, 0.008 y 0,030, inferiores a 0.05. Finalmente, en modelo general, la variable predictora “cultura organizacional” influye positivamente en la variable criterio “habilidades gerenciales”, pues su t de Student 9.879, con un p-valor de 0.000, inferior a 0.05. En conclusión, la cultura organizacional se relaciona positivamente con las habilidades gerenciales.
APA, Harvard, Vancouver, ISO, and other styles
3

Sales, Francisco Das Chagas Vieira, José Antonio Aleixo da Silva, Rinaldo Luiz Caraciolo Ferreira, and Fernando Henrique de Lima Gadelha. "AJUSTES DE MODELOS VOLUMÉTRICOS PARA O CLONE Eucalyptus grandis x E. urophylla CULTIVADOS NO AGRESTE DE PERNAMBUCO." FLORESTA 45, no. 4 (October 16, 2015): 663. http://dx.doi.org/10.5380/rf.v45i4.37594.

Full text
Abstract:
O presente trabalho teve como objetivo avaliar o ajuste de modelos volumétricos para um clone de Eucalyptus usando distribuição normal e t-Student, utilizando dados de um experimento implantado no Instituto Agronômico de Pernambuco (IPA) em São Bento do Una, PE. Para o ajuste dos modelos volumétricos de Silva e Bailey modificado, Chapman e Richard modificado, Schumacher e Hall e, Brody modificado, foram utilizados dados de 62 árvores cubadas rigorosamente pelo método de Smalian. Os critérios usados nas comparações das equações foi o valor ponderado (VP) entre o Índice de Ajuste corrigido (IAc) e o erro percentual absoluto médio (EPAM). De acordo com os resultados o modelo que mostrou melhores ajustes nas duas distribuições foi o de Schumacher e Hall, com melhores ajuste quando da distribuição t-Student. A distribuição t-Student promoveu melhorias nos ajustes das equações em relação à distribuição Normal, quando comparando as duas distribuições em cada equação.AbstractAdjustment of volumetric models for clone of Eucalyptus grandis x E. Urophylla grown on agreste, Pernambuco. This research aimed to evaluate the volumetric models fitting for Eucalyptus clone using normal and t-Student distributions, based on data from an experiment implanted at the Agronomic Institute of Pernambuco (IPA) in São Bento do Una, PE. In order to set the modified volumetric models of Silva and Bailey, modified Chapman and Richard, Schumacher and Hall, and modified Brody, we used data from 62 trees rigorously scaled by Smalian method. The criteria for equation comparing were the weighted value (PV) between the corrected index adjustment (IAc) and absolute mean error percentage (EPAM). According to the results, the model that best fits for the two distributions is Schumacher and Hall, with better adjustment related to the Student-t distribution. The t-Student distribution promoted improvements of equations regarding the Normal distribution, compared to the two distributions per equation.Keywords: Forest management; symmetric distributions; volume equations.
APA, Harvard, Vancouver, ISO, and other styles
4

Nugroho, Didit Budi, Agus Priyono, and Bambang Susanto. "SKEW NORMAL AND SKEW STUDENT-T DISTRIBUTIONS ON GARCH(1,1) MODEL." MEDIA STATISTIKA 14, no. 1 (April 16, 2021): 21–32. http://dx.doi.org/10.14710/medstat.14.1.21-32.

Full text
Abstract:
The Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) type models have become important tools in financial application since their ability to estimate the volatility of financial time series data. In the empirical financial literature, the presence of skewness and heavy-tails have impacts on how well the GARCH-type models able to capture the financial market volatility sufficiently. This study estimates the volatility of financial asset returns based on the GARCH(1,1) model assuming Skew Normal and Skew Student-t distributions for the returns errors. The models are applied to daily returns of FTSE100 and IBEX35 stock indices from January 2000 to December 2017. The model parameters are estimated by using the Generalized Reduced Gradient Non-Linear method in Excel’s Solver and also the Adaptive Random Walk Metropolis method implemented in Matlab. The estimation results from fitting the models to real data demonstrate that Excel’s Solver is a promising way for estimating the parameters of the GARCH(1,1) models with non-Normal distribution, indicated by the accuracy of the estimation of Excel’s Solver. The fitting performance of models is evaluated by using log-likelihood ratio test and it indicates that the GARCH(1,1) model with Skew Student-t distribution provides the best fitting, followed by Student-t, Skew-Normal, and Normal distributions.
APA, Harvard, Vancouver, ISO, and other styles
5

Prado, Naimara V. do, Miguel A. Uribe-Opazo, Manuel Galea, and Rosangela A. B. Assumpção. "Influência local em um modelo espacial linear da produtividade da soja utilizando distribuição t-Student." Engenharia Agrícola 33, no. 5 (October 2013): 1003–16. http://dx.doi.org/10.1590/s0100-69162013000500012.

Full text
Abstract:
O uso das ferramentas da geoestatística, aliadas à agricultura de precisão permitem o acompanhamento das áreas agrícolas produtoras de soja, estabelecendo as relações de dependência espacial entre os pontos amostrados. A modelagem da estrutura de variabilidade espacial possibilita a construção de mapas temáticos dos atributos estudados, utilizando como método de interpolação a krigagem. Porém, a presença de valores atípicos entre os elementos amostrais pode influenciar na construção e interpretação desses mapas. A distribuição de probabilidades t-Student tem sido utilizada na tentativa de diminuir a influência dos valores atípicos durante a estimativa dos parâmetros de dependência espacial, por ter caudas mais pesadas que a distribuição normal. A detecção dos valores influentes na área em estudo, por meio da análise de diagnósticos de influência local, confere maior confiabilidade na utilização dos mapas gerados, corroborando a aplicação de insumos. Deste modo, o objetivo deste trabalho foi aplicar as técnicas de influência local em dados espacialmente referenciados, com os modelos de perturbação aditiva e utilizando a matriz escala, considerando a distribuição t-Student n-variada. Foi utilizado um modelo espacial linear para o estudo de dados da produtividade da soja em função da altura média de plantas e do número médio de vagens por planta. As técnicas de influência local foram eficientes para detectar pontos que influenciam na escolha do modelo geoestatístico, nas estimativas dos parâmetros e na construção do mapa temático.
APA, Harvard, Vancouver, ISO, and other styles
6

Loschi, Rosangela H., Pilar L. Iglesias, and Reinaldo B. Arellano-Valle. "Predictivistic characterizations of multivariate student-t models." Journal of Multivariate Analysis 85, no. 1 (April 2003): 10–23. http://dx.doi.org/10.1016/s0047-259x(02)00034-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Nguyen, Hang T., and Ian T. Nabney. "Variational inference for Student-t MLP models." Neurocomputing 73, no. 16-18 (October 2010): 2989–97. http://dx.doi.org/10.1016/j.neucom.2010.07.009.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Valencia Salazar, Edilberto, Segundo Edilberto Vergara Medrano, Luis Carbajal García, and Manuel Jesús Sánchez Chero. "Aplicación del modelo 4MAT y su influencia en el rendimiento académico de cinemática en estudiantes universitarios." Revista Científica UNTRM: Ciencias Sociales y Humanidades 2, no. 2 (February 17, 2020): 55. http://dx.doi.org/10.25127/rcsh.20192.530.

Full text
Abstract:
<p>Se presentan resultados de la aplicación del Modelo 4MAT en el marco del estudio sobre estilos de aprendizaje y desempeño en la enseñanza de Cinemática del curso de Cinemática de Ingeniería Agroindustrial de la Universidad Nacional Intercultural de la Amazonía. Para lograrlo, se elaboró estrategias de enseñanza aprendizaje basados en los ocho pasos del Modelo 4MAT. Esta experiencia estuvo basada en el enfoque cuantitativo, de tipo aplicativa con diseño cuasi experimental. La muestra consistió de 36 estudiantes (18 del Grupo Experimental y 18 del Grupo Control) de una población de 250. El análisis de resultados se realizó con pruebas, T de Student y Wilcoxon. Se demostró que la aplicación del Modelo 4MAT influye significativamente en el rendimiento académico de estudiantes del ciclo II de la Universidad, aseveración que se sustenta en el análisis estadístico de T de Student, los estudiantes del grupo experimental obtuvieron mejores notas (Promedio 10,44) después del experimento respecto a los del grupo control (Promedio = 5,89); por lado, la significancia estadística p = 0, 00 &lt; 0,05 = α además (t = 1, c 154 &lt; t = 1, 74), significó aceptar la hipótesis de investigación. La aplicación del Modelo 4MAT influye también t significativamente en cuanto al cambio actitudinal positivo en los estudiantes.</p>
APA, Harvard, Vancouver, ISO, and other styles
9

Basso-Aránguiz, Matilde, Mario Bravo-Molina, Antonella Castro-Riquelme, and César Moraga-Contreras. "Propuesta de modelo tecnológico para Flipped Classroom (T-FliC) en educación superior." Revista Electrónica Educare 22, no. 2 (February 15, 2018): 1. http://dx.doi.org/10.15359/ree.22-2.2.

Full text
Abstract:
The Technology Model, called T-FliC is proposed for Flipped Classroom. The aim is to provide IT facilities to the aforementioned pedagogical model. This proposal may be implemented at different levels of higher education. T-FliC is primarily based on the use of free technology resources, especially Google applications such as Classroom, Drive, and YouTube, because they are widely used by students and teachers. This extensive use permits to replicate this model in different educational contexts. The T-FliC model incorporates five ICT phases, ranging from the planning of teaching-learning activities to continuous learning assessments. The implementation of the T-FliC Model includes the following phases: a digital class (learning outside the classroom) with asynchronous guidance of a virtual tutor; a workshop involving dynamic activities for collaborative work (classroom learning) guided by a tutor in person; and an ongoing technological tools evaluation process (clickers, portfolio, and forum) which will generate the digital records of the student learning path. This article includes a bibliographic review of the role of ICT in the education processes and the fundamentals of the Flipped Classroom (FC) methodology. In the paper are included FC implementation experiences in higher education, followed by the presentation of the T-FliC Model as a technological proposal for this methodology. Finally, the conclusions present reflections on the proposal.
APA, Harvard, Vancouver, ISO, and other styles
10

Pamplona, Edgar, Clóvis Fiirst, Nelson Hein, and Vinícius Costa da Silva Zonatto. "Desempenho do Modelo Arma na Previsão das Receitas Orçamentárias dos Municípios do Estado do Paraná." Administração Pública e Gestão Social 11, no. 1 (January 1, 2019): 92–103. http://dx.doi.org/10.21118/apgs.v11i1.1487.

Full text
Abstract:
O estudo investiga o desempenho do modelo ARMA na previsão das receitas orçamentárias dos municípios do Estado do Paraná, em comparação com o modelo proposto pela Secretaria do Orçamento Federal. Pesquisa descritiva, com abordagem quantitativa e análise documental, foi realizada com amostra de 120 municípios. Os achados apontam que o modelo ARMA, no geral, apresentou melhor desempenho na previsão das receitas públicas, com erro médio de 7,05%. Das 120 observações realizadas, o modelo ARMA obteve desempenho superior em 74 casos (61,67%), enquanto que o modelo SOF foi melhor em 46 oportunidades (38,33%). Os erros médios dos dois modelos testados na pesquisa foram submetidos ao teste de diferença de médias (teste t de student), constatando-se que as previsões de ambos os modelos são diferentes estatisticamente ao nível de significância de 5%. Assim, pode-se concluir que o modelo ARMA apresentou melhor qualidade nas previsões das receitas em comparação ao modelo SOF.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Modelo t de Student"

1

Lopes, Jocely Nascimento. "Misturas de distribuições T de student assimétricas." Universidade Federal do Amazonas, 2008. http://tede.ufam.edu.br/handle/tede/5226.

Full text
Abstract:
Submitted by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-09-30T13:45:51Z No. of bitstreams: 1 Dissertação - Jocely Lopes.pdf: 2989672 bytes, checksum: 6e22a80fdd1f21213e48a66c75d7c923 (MD5)
Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-09-30T13:46:06Z (GMT) No. of bitstreams: 1 Dissertação - Jocely Lopes.pdf: 2989672 bytes, checksum: 6e22a80fdd1f21213e48a66c75d7c923 (MD5)
Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-09-30T13:46:22Z (GMT) No. of bitstreams: 1 Dissertação - Jocely Lopes.pdf: 2989672 bytes, checksum: 6e22a80fdd1f21213e48a66c75d7c923 (MD5)
Made available in DSpace on 2016-09-30T13:46:22Z (GMT). No. of bitstreams: 1 Dissertação - Jocely Lopes.pdf: 2989672 bytes, checksum: 6e22a80fdd1f21213e48a66c75d7c923 (MD5) Previous issue date: 2008-12-22
Não informada
In this work we consider the estimation of parameters of a nite mixture of skew Student-t distributions, via EM algorithm. The main goals of this dissertation is to show a detailed description of the EM algorithm applied to this model and to evaluate the consistency of the estimator. A data set concerning the Gross Domestic Product per capita (Human Development Report), previously studied in the related literature, is analyzed.
Este trabalho trata do problema de estimar parâmetros de uma mistura nita de densidades t-assimétricas. Como ferramenta para a estimação foi usado o algoritmo EM. Foi avaliada a consistência desses estimadores e realizado um experimento de aplicação da teoria desenvolvida para uma modelagem com dados reais utilizando um conjunto analisado anteriormente na literatura, relativo ao PIB per capita. Os objetivos centrais desse trabalho são apresentar uma descrição detalhada do método de estimação, via algoritmo EM, dos parâmetros do modelo nito de mistura de densidades t-assimétricas e avaliar através de um estudo de simulação se o estimador obtido é consistente.
APA, Harvard, Vancouver, ISO, and other styles
2

Cintra, Flávia Maria Ravagnani Neves. "Aplicação do modelo t-student para análise dos resultados de ensaios de proficiência." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-03012018-171250/.

Full text
Abstract:
Os Ensaios de Proficiência por comparação interlaboratorial têm sido um importante mecanismo para controlar a consistência dos laboratórios. Instituições do governo, como o INMETRO, têm utilizado tais mecanismos para monitorar a qualidade dos serviços prestados pelos laboratórios da Rede Brasileira de Laboratórios (RBL) e da Rede Brasileira de Calibração (RBC). Atualmente, os métodos estatísticos utilizados para analisar os resultados dos Ensaios de Proficiência estão escritos em normas técnicas, como o ISO/IEC Guide 43-1. Recentemente, Leão, Aoki e Silva (2002) propuseram um método de regressão para testar a competência dos laboratórios, utilizando a distribuição normal multivariada para modelar os dados e estabelecer testes estatísticos. Como em medições a presença de valores extremos é constante, vamos modelar os dados utilizando a distribuição t-student, para acomodar tais valores extremos. Neste modelo, estamos interessados em estimar o grau de liberdade e o parâmetro de tendência da medição do laboratório com respeito ao valor de referência, já que os laboratórios vão utilizar sistemas de medições similares para medir o mesmo item, com incertezas determinadas por um processo de calibração. Encontraremos os estimadores de máxima verossimilhança e de momentos para estes dois parâmetros e vamos desenvolver um teste para avaliarmos a consistência das medições dos laboratórios. No final, a título de aplicação, vamos analisar os dados obtidos pela REMESP (Rede de Metrologia de São Paulo) na área de eletricidade, onde vamos medir a tensão DC de um multímetro digital.
The proficiency essays by interlaboratorial comparison have been an important mechanism to control the consistency of the measurements of the laboratories. Government institutions, such as INMETRO, have used such mechanisms to monitor the quality of the laboratories services supplied by the Laboratories Brazilian Network (RBL) and by the Calibration Brazilian Network (RBC). Currently. the statistical methods used to analyze the results of the Proficiency Essays are described in technical norms, like the ISO/IEC Guide 43-1. Recently, Leão, Aoki and Silva (2002) proposed a regression method to test the laboratories ability, using the multivariate normal distribution to fit the data and to establish statistical tests. Like in measurements the presence of extreme values is constant, we are modelling the data using the multivariate t-student distribution, to accommodate such extreme values. In this model, we are interested in estimating the degrees of freedom and the tendency parameter of the laboratory measurement relating to the reference value, since the laboratories are using similar measurements systems to measure the same item, with standard deviation determined by a calibration process. We are finding the maximum likelihood and moments estimators for these two parameters and are developing a test to evaluate the laboratories measurements consistency. At the end, we are analyzing the obtained data for the REMESP (São Paulo Metrology Network) in the electrical area, where we are measuring the digital multimeter DC tension.
APA, Harvard, Vancouver, ISO, and other styles
3

Paczkowski, Remi. "Monte Carlo Examination of Static and Dynamic Student t Regression Models." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/38691.

Full text
Abstract:
This dissertation examines a number of issues related to Static and Dynamic Student t Regression Models. The Static Student t Regression Model is derived and transformed to an operational form. The operational form is then examined in a series of Monte Carlo experiments. The model is judged based on its usefulness for estimation and testing and its ability to model the heteroskedastic conditional variance. It is also compared with the traditional Normal Linear Regression Model. Subsequently the analysis is broadened to a dynamic setup. The Student t Autoregressive Model is derived and a number of its operational forms are considered. Three forms are selected for a detailed examination in a series of Monte Carlo experiments. The models’ usefulness for estimation and testing is evaluated, as well as their ability to model the conditional variance. The models are also compared with the traditional Dynamic Linear Regression Model.
Ph. D.
APA, Harvard, Vancouver, ISO, and other styles
4

Rama, Vishal. "Estimating stochastic volatility models with student-t distributed errors." Master's thesis, Faculty of Science, 2020. http://hdl.handle.net/11427/32390.

Full text
Abstract:
This dissertation aims to extend on the idea of Bollerslev (1987), estimating ARCH models with Student-t distributed errors, to estimating Stochastic Volatility (SV) models with Student-t distributed errors. It is unclear whether Gaussian distributed errors sufficiently account for the observed leptokurtosis in financial time series and hence the extension to examine Student-t distributed errors for these models. The quasi-maximum likelihood estimation approach introduced by Harvey (1989) and the conventional Kalman filter technique are described so that the SV model with Gaussian distributed errors and SV model with Student-t distributed errors can be estimated. Estimation of GARCH (1,1) models is also described using the method maximum likelihood. The empirical study estimated four models using data on four different share return series and one index return, namely: Anglo American, BHP, FirstRand, Standard Bank Group and JSE Top 40 index. The GARCH and SV model with Student-t distributed errors both perform best on the series examined in this dissertation. The metric used to determine the best performing model was the Akaike information criterion (AIC).
APA, Harvard, Vancouver, ISO, and other styles
5

Busato, Erick Andrade. "Função de acoplamento t-Student assimetrica : modelagem de dependencia assimetrica." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/305857.

Full text
Abstract:
Orientador: Luiz Koodi Hotta
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
Made available in DSpace on 2018-08-12T14:00:24Z (GMT). No. of bitstreams: 1 Busato_ErickAndrade_M.pdf: 4413458 bytes, checksum: b9c4c39b4639c19e685bae736fc86c4f (MD5) Previous issue date: 2008
Resumo: A família de distribuições t-Student Assimétrica, construída a partir da mistura em média e variância da distribuição normal multivariada com a distribuição Inversa Gama possui propriedades desejáveis de flexibilidade para as mais diversas formas de assimetria. Essas propriedades são exploradas na construção de funções de acoplamento que possuem dependência assimétrica. Neste trabalho são estudadas as características e propriedades da distribuição t-Student Assimétrica e a construção da respectiva função de acoplamento, fazendo-se uma apresentação de diferentes estruturas de dependência que pode originar, incluindo assimetrias da dependência nas caudas. São apresentados métodos de estimação de parâmetros das funções de acoplamento, com aplicações até a terceira dimensão da cópula. Essa função de acoplamento é utilizada para compor um modelo ARMA-GARCHCópula com marginais de distribuição t-Student Assimétrica, que será ajustado para os logretornos de preços do Petróleo e da Gasolina, e log-retornos do Índice de Óleo AMEX, buscando o melhor ajuste, principalmente, para a dependência nas caudas das distribuições de preços. Esse modelo será comparado, através de medidas de Valor em Risco e AIC, além de outras medidas de bondade de ajuste, com o modelo de Função de Acoplamento t-Student Simétrico.
Abstract: The Skewed t-Student distribution family, constructed upon the multivariate normal mixture distribution, known as mean-variance mixture, composed with the Inverse-Gamma distribution, has many desirable flexibility properties for many distribution asymmetry structures. These properties are explored by constructing copula functions with asymmetric dependence. In this work the properties and characteristics of the Skewed t-Student distribution and the construction of a respective copula function are studied, presenting different dependence structures that the copula function generates, including tail dependence asymmetry. Parameter estimation methods are presented for the copula, with applications up to the 3rd dimension. This copula function is used to compose an ARMAGARCH- Copula model with Skewed t-Student marginal distribution that is adjusted to logreturns of Petroleum and Gasoline prices and log-returns of the AMEX Oil Index, emphasizing the return's tail distribution. The model will be compared, by the means of the VaR (Value at Risk) and Akaike's Information Criterion, along with other Goodness-of-fit measures, with models based on the Symmetric t-Student Copula.
Mestrado
Mestre em Estatística
APA, Harvard, Vancouver, ISO, and other styles
6

Rahman, Azizur. "Bayesian prediction distributions for some linear models under student-t errors." University of Southern Queensland, Faculty of Sciences, 2007. http://eprints.usq.edu.au/archive/00003581/.

Full text
Abstract:
[Abstract]: This thesis investigates the prediction distributions of future response(s), conditional on a set of realized responses for some linear models havingstudent-t error distributions by the Bayesian approach under the uniform priors. The models considered in the thesis are the multiple regression modelwith multivariate-t errors and the multivariate simple as well as multiple re-gression models with matrix-T errors. For the multiple regression model, results reveal that the prediction distribution of a single future response anda set of future responses are a univariate and multivariate Student-t distributions respectively with appropriate location, scale and shape parameters.The shape parameter of these prediction distributions depend on the size of the realized responses vector and the dimension of the regression parameters' vector, but do not depend on the degrees of freedom of the error distribu-tion. In the multivariate case, the distribution of a future responses matrix from the future model, conditional on observed responses matrix from the realized model for both the multivariate simple and multiple regression mod-els is matrix-T distribution with appropriate location matrix, scale factors and shape parameter. The results for both of these models indicate that prediction distributions depend on the realized responses only through the sample regression matrix and the sample residual sum of squares and products matrix. The prediction distribution also depends on the design matricesof the realized as well as future models. The shape parameter of the prediction distribution of the future responses matrix depends on size of the realized sample and the number of regression parameters of the multivariatemodel. Furthermore, the prediction distributions are derived by the Bayesian method as multivariate-t and matrix-T are identical to those obtained under normal errors' distribution by the di®erent statistical methods such as the classical, structural distribution and structural relations of the model approaches. This indicates not only the inference robustness with respect todepartures from normal error to Student-t error distributions, but also indicates that the Bayesian approach with a uniform prior is competitive withother statistical methods in the derivation of prediction distribution.
APA, Harvard, Vancouver, ISO, and other styles
7

Assumpção, Rosangela Aparecida Botinha. "Influência local em modelos geoestatísticos T-Student com aplicações a dados agrícolas." Universidade Estadual do Oeste do Parana, 2010. http://tede.unioeste.br:8080/tede/handle/tede/374.

Full text
Abstract:
Made available in DSpace on 2017-05-12T14:48:22Z (GMT). No. of bitstreams: 1 Rosangela_texto.pdf: 2310887 bytes, checksum: d9e69eaef22ee697283c66446001b19e (MD5) Previous issue date: 2010-12-16
The presence of inconsistent observations make it improper to consider the gaussian process, as it is found in the literature. This process should be replaced by models of the symmetric distribution classes, such as the t-student distribution, which incorporates additional parameters to reduce the influence of inconsistent points. This work has developed the EM algorithm for estimating the structure of the spatial dependence of the parameters and of the spatial linear model, assuming that the process shows t-student n-varied distribution. This distribution has the degree of freedom v as the additional parameter, which has been considered to be fixed in this research. Techniques to diagnose influence are used after the estimation of parameters, in order to assess the quality of the adjustment of the model by the assumptions made and for the robustness of the results of the estimates when there are disturbances in the model or data. In the present work, diagnostic techniques for the assessment of local influence in linear spatial models have been developed, considering the process with t-student n-varied distribution. The usual diagnostic technique evaluates the withdrawing of the likelihood rate by the function of the likelihood logarithm. In this proposal, in addition to considering the usual technique, we use the withdrawing of the likelihood by Q-displacement of the complete likelihood. The application of the usual technique and of the one proposed here are illustrated through the analyses of both simulated and real data, provenient of agricultural experiments.
A presença de observações discrepantes torna imprópria a análise do processo gaussiano, sendo assim, como é encontrado na literatura, esse processo deve ser substituído por modelos da classe das distribuições simétricas, tal como a distribuição t-student, que incorpora parâmetros adicionais para reduzir a influência dos pontos discrepantes. Neste trabalho, assumiu-se que o processo apresenta distribuição t-student n-variada. Essa distribuição tem como parâmetro adicional o grau de liberdade v, que aqui considerou-se fixo. Dessa forma, desenvolveu-se o algoritmo EM e o algoritmo de NR para a estimação dos parâmetros da estrutura de dependência espacial e do modelo espacial linear. Após a estimação dos parâmetros, utilizou-se duas técnicas de diagnósticos de influência local, ambas com o intuito de avaliar a qualidade do ajuste do modelo pelas suposições feitas e pela robustez dos resultados das estimativas quando há perturbações no modelo ou nos dados. A primeira técnica, denominada "usual", já utilizada por diversos autores, avalia o afastamento da verossimilhança pela função do logaritmo da verossimilhança e a segunda técnica que aqui apresentamos propõe a análise de influência local pelo Q-afastamento da função de verossimilhança para dados completos. Essas técnicas permitiram verificar a influência no afastamento da verossimilhança, na matriz de covariância, no preditor linear e nos valores preditos por meio da análise gráfica. Para ilustrar a aplicação da técnica usual e da nossa proposta, realizou-se a análise de dados simulados e dados reais provenientes de experimentos agrícolas.
APA, Harvard, Vancouver, ISO, and other styles
8

Souza, Aline Campos Reis de. "Modelos de regressão linear heteroscedásticos com erros t-Student : uma abordagem bayesiana objetiva." Universidade Federal de São Carlos, 2016. https://repositorio.ufscar.br/handle/ufscar/7540.

Full text
Abstract:
Submitted by Luciana Sebin (lusebin@ufscar.br) on 2016-09-26T18:57:40Z No. of bitstreams: 1 DissACRS.pdf: 1390452 bytes, checksum: a5365fdbf745228c0174f2643b3f7267 (MD5)
Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-09-27T19:59:56Z (GMT) No. of bitstreams: 1 DissACRS.pdf: 1390452 bytes, checksum: a5365fdbf745228c0174f2643b3f7267 (MD5)
Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-09-27T20:00:01Z (GMT) No. of bitstreams: 1 DissACRS.pdf: 1390452 bytes, checksum: a5365fdbf745228c0174f2643b3f7267 (MD5)
Made available in DSpace on 2016-09-27T20:00:08Z (GMT). No. of bitstreams: 1 DissACRS.pdf: 1390452 bytes, checksum: a5365fdbf745228c0174f2643b3f7267 (MD5) Previous issue date: 2016-02-18
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
In this work , we present an extension of the objective bayesian analysis made in Fonseca et al. (2008), based on Je reys priors for linear regression models with Student t errors, for which we consider the heteroscedasticity assumption. We show that the posterior distribution generated by the proposed Je reys prior, is proper. Through simulation study , we analyzed the frequentist properties of the bayesian estimators obtained. Then we tested the robustness of the model through disturbances in the response variable by comparing its performance with those obtained under another prior distributions proposed in the literature. Finally, a real data set is used to analyze the performance of the proposed model . We detected possible in uential points through the Kullback -Leibler divergence measure, and used the selection model criterias EAIC, EBIC, DIC and LPML in order to compare the models.
Neste trabalho, apresentamos uma extensão da análise bayesiana objetiva feita em Fonseca et al. (2008), baseada nas distribuicões a priori de Je reys para o modelo de regressão linear com erros t-Student, para os quais consideramos a suposicão de heteoscedasticidade. Mostramos que a distribuiçãoo a posteriori dos parâmetros do modelo regressão gerada pela distribuição a priori e própria. Através de um estudo de simulação, avaliamos as propriedades frequentistas dos estimadores bayesianos e comparamos os resultados com outras distribuições a priori encontradas na literatura. Além disso, uma análise de diagnóstico baseada na medida de divergência Kullback-Leiber e desenvolvida com analidade de estudar a robustez das estimativas na presença de observações atípicas. Finalmente, um conjunto de dados reais e utilizado para o ajuste do modelo proposto.
APA, Harvard, Vancouver, ISO, and other styles
9

Matos, Larissa Avila 1987. "Modelos lineares e não lineares de efeitos mistos para respostas censuradas usando as distribuições normal e t-Student multivariadas." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306684.

Full text
Abstract:
Orientador: Víctor Hugo Lachos Dávila
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
Made available in DSpace on 2018-08-20T06:44:43Z (GMT). No. of bitstreams: 1 Matos_LarissaAvila_M.pdf: 2008810 bytes, checksum: 0aee0c4f4bbf58ba67490d26cdd300ba (MD5) Previous issue date: 2012
Resumo: Modelos mistos são geralmente usados para representar dados longitudinais ou de medidas repetidas. Uma complicação adicional surge quando a resposta é censurada, por exemplo, devido aos limites de quantificação do ensaio utilizado. Distribuições normais para os efeitos aleatórios e os erros residuais são geralmente assumidas, mas tais pressupostos fazem as inferências vulneráveis, 'a presença de outliers. Motivados por uma preocupação da sensibilidade para potenciais outliers ou dados com caudas mais pesadas do que a normal, pretendemos desenvolver nessa dissertação, inferência para modelos lineares e não lineares de efeito misto censurados (NLMEC / LMEC) com base na distribui ção t- Student multivariada, sendo uma alternativa flexível ao uso da distribuição normal correspondente. Propomos um algoritmo ECM para computar as estimativas de máxima verossimilhança para os NLMEC / LMEC. Este algoritmo utiliza expressões fechadas no passo-E, que se baseia em fórmulas para a média e a variância de uma distribui ção t-multivariada truncada. O algoritmo proposto é implementado, pacote tlmec do R. Também propomos aqui um algoritmo ECM exato para os modelos lineares e não lineares de efeito misto censurados, com base na distribuição normal multivariada, que nos permite desenvolver análise de influência local para modelos de efeito misto com base na esperança condicional da função log-verossilhança dos dados completos. Os procedimentos desenvolvidos são ilustrados com a análise longitudinal da carga viral do HIV, apresentada em dois estudos recentes sobre a AIDS
Abstract: Mixed models are commonly used to represent longitudinal or repeated measures data. An additional complication arises when the response is censored, for example, due to limits of quantification of the assay used. Normal distributions for random effects and residual errors are usually assumed, but such assumptions make inferences vulnerable to the presence of outliers. Motivated by a concern of sensitivity to potential outliers or data with tails longer-than-normal, we aim to develop in this dissertation inference for linear and nonlinear mixed effects models with censored response (NLMEC/LMEC) based on the multivariate Student-t distribution, being a flexible alternative to the use of the corresponding normal distribution. We propose an ECM algorithm for computing the maximum likelihood estimates for NLMEC/LMEC. This algorithm uses closed-form expressions at the E-step, which relies on formulas for the mean and variance of a truncated multivariate-t distribution. The proposed algorithm is implemented in the R package tlmec. We also propose here an exact ECM algorithm for linear and nonlinear mixed effects models with censored response based on the multivariate normal distribution, which enable us to developed local influence analysis for mixed effects models on the basis of the conditional expectation of the complete-data log-likelihood function. The developed procedures are illustrated with two case studies, involving the analysis of longitudinal HIV viral load in two recent AIDS studies
Mestrado
Estatistica
Mestre em Estatística
APA, Harvard, Vancouver, ISO, and other styles
10

Mazviona, Batsirai Winmore. "Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution." Master's thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/12344.

Full text
Abstract:
Includes bibliographical references.
This thesis focuses on forecasting the volatility of daily returns using a double Markov switching GARCH model with a skewed Student-t error distribution. The model was applied to individual shares obtained from the Johannesburg Stock Exchange (JSE). The Bayesian approach which uses Markov Chain Monte Carlo was used to estimate the unknown parameters in the model. The double Markov switching GARCH model was compared to a GARCH(1,1) model. Value at risk thresholds and violations ratios were computed leading to the ranking of the GARCH and double Markov switching GARCH models. The results showed that double Markov switching GARCH model performs similarly to the GARCH model based on the ranking technique employed in this thesis.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Modelo t de Student"

1

Bilodeau, M. Stein estimation under elliptical distribution, power of F-tests under student-T distribution and tests of correlation in USR models. [Toronto]: [s.n.], 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Trejos, Alfredo. Modelo T: Antología personal, 1999-2009. Guatemala: Catafixia, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Modelo T: Antología personal, 1999-2009. Guatemala: Catafixia, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Rausch, Monica. Henry Ford y el automóvil Modelo T. Milwaukee, WI: Weekly Reader Early Learning Library, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Ahsanullah, Mohammad, B. M. Golam Kibria, and Mohammad Shakil. Normal and Student´s t Distributions and Their Applications. Paris: Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-061-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Ceuster, Marc de. Diagnostic checking of estimation with a Student-t error density. Antwerpen: Universiteit Antwerpen, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Lu, Qiaoping. Medienkompetenz von Studierenden an chinesischen Hochschulen. Wiesbaden: VS, Verl. fu r Sozialwiss., 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Bilodeau, Martin R. Stein estimation under elliptical distribution, power of F-tests under student-T distribution and tests of correlation in Sur models. 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Ballman, Terry L., Bill VanPatten, and James F. Lee. Student Audiocassette Program t/a Vistazos. McGraw-Hill Humanities/Social Sciences/Languages, 2001.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Magnan, Sally Sieloff. Student Video Manual T/A Paroles. Wiley, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Modelo t de Student"

1

Kobayashi, Taisuke. "Variational Deep Embedding with Regularized Student-t Mixture Model." In Lecture Notes in Computer Science, 443–55. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30508-6_36.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Mohammad-Djafari, Ali. "Variational Bayesian Approximation Method for Classification and Clustering with a Mixture of Student-t Model." In Lecture Notes in Computer Science, 723–31. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25040-3_77.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Frost, Irasianty. "Beispiel: Student-t-Test." In essentials, 13–15. Wiesbaden: Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-16258-0_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Ahsanullah, Mohammad, B. M. Golam Kibria, and Mohammad Shakil. "Student’s $$t$$ t Distribution." In Normal and Student´s t Distributions and Their Applications, 51–62. Paris: Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-061-4_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Towndrow, Phillip Alexander, and Galyna Kogut. "Student T. Rushing, Busy, Crowded." In Studies in Singapore Education: Research, Innovation & Practice, 111–17. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8727-6_11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Grigelionis, Bronius. "Student-Lévy Processes." In Student’s t-Distribution and Related Stochastic Processes, 41–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31146-8_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Grigelionis, Bronius. "Student Diffusion Processes." In Student’s t-Distribution and Related Stochastic Processes, 57–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31146-8_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Grigelionis, Bronius. "Student OU-Type Processes." In Student’s t-Distribution and Related Stochastic Processes, 51–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31146-8_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Li, Xiaoyan, and Jinwen Ma. "Non-central Student-t Mixture of Student-t Processes for Robust Regression and Prediction." In Intelligent Computing Theories and Application, 499–511. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84522-3_41.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Ahsanullah, Mohammad, B. M. Golam Kibria, and Mohammad Shakil. "Product of the Normal and Student’s $$t$$ t Densities." In Normal and Student´s t Distributions and Their Applications, 103–11. Paris: Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-061-4_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Modelo t de Student"

1

Takahashi, Hiroshi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, and Satoshi Yagi. "Student-t Variational Autoencoder for Robust Density Estimation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/374.

Full text
Abstract:
We propose a robust multivariate density estimator based on the variational autoencoder (VAE). The VAE is a powerful deep generative model, and used for multivariate density estimation. With the original VAE, the distribution of observed continuous variables is assumed to be a Gaussian, where its mean and variance are modeled by deep neural networks taking latent variables as their inputs. This distribution is called the decoder. However, the training of VAE often becomes unstable. One reason is that the decoder of VAE is sensitive to the error between the data point and its estimated mean when its estimated variance is almost zero. We solve this instability problem by making the decoder robust to the error using a Bayesian approach to the variance estimation: we set a prior for the variance of the Gaussian decoder, and marginalize it out analytically, which leads to proposing the Student-t VAE. Numerical experiments with various datasets show that training of the Student-t VAE is robust, and the Student-t VAE achieves high density estimation performance.
APA, Harvard, Vancouver, ISO, and other styles
2

Mousazadeh, Saman, and Mahmood Karimi. "Parameter Estimation for Student-t ARCH Model using MDL Criterion." In 2007 IEEE International Conference on Signal Processing and Communications. IEEE, 2007. http://dx.doi.org/10.1109/icspc.2007.4728379.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Kukovec, Rok, Špela Pečnik, Iztok Fister Jr., and Sašo Karakatič. "Adversarial Image Perturbation with a Genetic Algorithm." In 7th Student Computer Science Research Conference. University of Maribor Press, 2021. http://dx.doi.org/10.18690/978-961-286-516-0.6.

Full text
Abstract:
The quality of image recognition with neural network models relies heavily on filters and parameters optimized through the training process. These filters are di˙erent compared to how humans see and recognize objects around them. The di˙erence in machine and human recognition yields a noticeable gap, which is prone to exploitation. The workings of these algorithms can be compromised with adversarial perturbations of images. This is where images are seemingly modified imperceptibly, such that humans see little to no di˙erence, but the neural network classifies t he m otif i ncorrectly. This paper explores the adversarial image modifica-tion with an evolutionary algorithm, so that the AlexNet convolutional neural network cannot recognize previously clear motifs while preserving the human perceptibility of the image. The ex-periment was implemented in Python and tested on the ILSVRC dataset. Original images and their recreated counterparts were compared and contrasted using visual assessment and statistical metrics. The findings s uggest t hat t he human eye, without prior knowledge, will hardly spot the di˙erence compared to the original images.
APA, Harvard, Vancouver, ISO, and other styles
4

Boenninghoff, Benedikt, Steffen Zeiler, Robert Nickel, and Dorothea Kolossa. "Variational Autoencoder with Embedded Student-t Mixture Model for Authorship Attribution." In Proceedings of the 28th International Conference on Computational Linguistics. Stroudsburg, PA, USA: International Committee on Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.coling-main.45.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Boenninghoff, Benedikt, Steffen Zeiler, Robert Nickel, and Dorothea Kolossa. "Variational Autoencoder with Embedded Student-t Mixture Model for Authorship Attribution." In Proceedings of the 28th International Conference on Computational Linguistics. Stroudsburg, PA, USA: International Committee on Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.coling-main.45.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Ciancarini, Paolo, Caroline Dos, and Sara Zuppiroli. "A double comparative study: Process models and student skills." In 2013 IEEE 26th Conference on Software Engineering Education and Training - (CSEE&T). IEEE, 2013. http://dx.doi.org/10.1109/cseet.2013.6595250.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Nugroho, Didit Budi, and Bambang Susanto. "Volatility modeling for IDR exchange rate through APARCH model with student-t distribution." In THE 4TH INTERNATIONAL CONFERENCE ON RESEARCH, IMPLEMENTATION, AND EDUCATION OF MATHEMATICS AND SCIENCE (4TH ICRIEMS): Research and Education for Developing Scientific Attitude in Sciences And Mathematics. Author(s), 2017. http://dx.doi.org/10.1063/1.4995120.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Azevedo, Caio L. N., and Helio S. Migon. "Bayesian inference in an item response theory model with a generalized student t link function." In XI BRAZILIAN MEETING ON BAYESIAN STATISTICS: EBEB 2012. AIP, 2012. http://dx.doi.org/10.1063/1.4759588.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Berinšterová, Marianna, Miroslava Bozogáňová, Monika Magdová, Jana Kapová, and Katarína Fuchsová. "PROCRASTINATION AND SELF-CONCEPT IN MORE/LESS CONSCIENTIOUS STUDENTS." In International Psychological Applications Conference and Trends. inScience Press, 2021. http://dx.doi.org/10.36315/2021inpact034.

Full text
Abstract:
"Given its significant negative consequences for university students, procrastination has been studied extensively and shown to be associated with conscientiousness as a personality trait. Involving 333 university students doing teacher training programmes (68.5% female; Mage=20.51 (SD=1.61); 83.48% undergraduates doing a bachelor’s degree), our study aimed to explore the association between procrastination among more/less conscientious students and selected self-concept variables (self-control, self-efficacy, etc.). Our questionnaire was based on the Ten-Item Personality Inventory (Gosling, Rentfrow, Swann, 2003), the Self-Control Scale (Finkenauer, Engels, Baumeister, 2005), the Self-efficacy Scale (Ko?š, Hefteyova, Schwarzer, Jerusalem, 1993), and the Procrastination Scale for Student Populations (Gabrhelík, 2008); our control variables were gender and well- being (Subjective Well-Being Scale, Chan-Hoong, Soon, 2011). The sample was divided into two groups – (1) less conscientious and (2) more conscientious) – using the method of visual binning in SPSS 20. A t-test for independent samples and linear regression were used for data analysis. The less conscientious students in our sample reported a higher level of procrastination (t=6.479; df=310; p?0.001; Cohen's d=0.681). A linear model was conducted for both groups (the dependent variable being the level of procrastination, the independent variables being gender and the levels of self-control, self-efficacy, and well-being). Both models were significant ((1) F=8.449; p?0.001; R2=32.6; (2) F= 7.277; p?0.001; R2=25.7). Among the less conscientious students, the levels of self-control (?=-0.546; t=-5.262; p?0.001) and self-efficacy (?=-0.238; t=-2.092; p?0.001) were negatively associated with procrastination. Among the more conscientious students, the level of self-control (?=0.404; t=-3.929; p?0.001) was negatively associated with procrastination and “being a man” (0–man; 1–woman) (?=-0.307; t=-3.219; p?0.05) was significantly associated with the level of procrastination. The results of our study show trait and personality differences in the level of procrastination, highlighting the importance of self-control and self-efficacy development among university students. Interactive programmes with an impact on students’ self-concept can be a significant contribution to students’ ability to cope with their study requirements effectively. It could be argued that the limits of this study include cross-sectional and self-reported data."
APA, Harvard, Vancouver, ISO, and other styles
10

Xiao, Angran, Gaffar Gailani, and Shaojin Zhang. "Assessing the Educational Effectiveness of a System Engineering Software in Capstone Design Projects." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-87640.

Full text
Abstract:
The increasing complexity of engineering and technology requires that students master an increasing amount of abstract knowledge to remain competitive in today’s job market. However, today’s students find it difficult to create mental images of abstract concepts, due to lack of real world experience. This problem is more evident in advanced design classes teaching product design concepts and methodologies. In this paper, we introduce a system engineering software package that is used in our capstone design class, with which students are able to create their own framework of product development activities, control information flows, and manage tools and engineering models in each activity. This allows them to plan out and manage their projects using the design methodologies that they learned in class. We assessed student learning in the capstone design class for the last 7 semesters. Independent Samples t-Test and factorial ANOVA are used to analyze the student performance before and after using the software package. We have observed that in the design classes, the system engineering software enables students to practice design methodologies by visualizing and managing product development processes. This helps students not only understand the abstract design methodologies, but also apply the methodologies to their projects and accomplish them more efficiently.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Modelo t de Student' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography