Relevant bibliographies by topics / Skew-t

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Academic literature on the topic 'Skew-t'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Skew-t"

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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 (2021): 21–32. http://dx.doi.org/10.14710/medstat.14.1.21-32.

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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 d
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GUPTA, A. K. "MULTIVARIATE SKEW t -DISTRIBUTION." Statistics: A Journal of Theoretical and Applied Statistics 37, no. 4 (2003): 1. http://dx.doi.org/10.1080/0233188031000123771.

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Lee, Sharon X., and Geoffrey J. McLachlan. "On mixtures of skew normal and skew $$t$$ -distributions." Advances in Data Analysis and Classification 7, no. 3 (2013): 241–66. http://dx.doi.org/10.1007/s11634-013-0132-8.

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Chamroukhi, F. "Skew t mixture of experts." Neurocomputing 266 (November 2017): 390–408. http://dx.doi.org/10.1016/j.neucom.2017.05.044.

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Acitas, Sukru, Birdal Senoglu, and Olcay Arslan. "Alpha-Skew Generalized t Distribution." Revista Colombiana de Estadística 38, no. 2 (2015): 371–84. http://dx.doi.org/10.15446/rce.v38n2.51665.

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<p>The alpha-skew normal (ASN) distribution has been proposed recently in the literature by using standard normal distribution and a skewing approach. Although ASN distribution is able to model both skew and bimodal data, it is shortcoming when data has thinner or thicker tails than normal. Therefore, we propose an alpha-skew generalized t (ASGT) by using the generalized t (GT) distribution and a new skewing procedure. From this point of view, ASGT can be seen as an alternative skew version of GT distribution. However, ASGT differs from the previous skew versions of GT distribution since
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Dey, Kumar, Chandra Paul та Bijan Davvaz. "On gamma-rings with (σ, t )-skew-commuting and (σ, t )-skew-centralizing mappings". Kragujevac Journal of Mathematics 42, № 1 (2018): 41–50. http://dx.doi.org/10.5937/kgjmath1801041d.

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Kollo, Tõnu, Meelis Käärik, and Anne Selart. "Multivariate Skew t-Distribution: Asymptotics for Parameter Estimators and Extension to Skew t-Copula." Symmetry 13, no. 6 (2021): 1059. http://dx.doi.org/10.3390/sym13061059.

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Symmetric elliptical distributions have been intensively used in data modeling and robustness studies. The area of applications was considerably widened after transforming elliptical distributions into the skew elliptical ones that preserve several good properties of the corresponding symmetric distributions and increase possibilities of data modeling. We consider three-parameter p-variate skew t-distribution where p-vector μ is the location parameter, Σ:p×p is the positive definite scale parameter, p-vector α is the skewness or shape parameter, and the number of degrees of freedom ν is fixed.
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EROĞLU İNAN, Gültaç. "Change-constrained stochastic programming problem with normal, t and skew normal, skew t distributions." Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics 70, no. 1 (2021): 180–93. http://dx.doi.org/10.31801/cfsuasmas.685733.

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Punathumparambath, Bindu. "The multivariate skew-slash t and skew-slash Cauchy distributions." Model Assisted Statistics and Applications 7, no. 1 (2012): 33–40. http://dx.doi.org/10.3233/mas-2011-0199.

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Son, Sookyoung, Hyunjung Lee, Yoona Jang, Junyeong Yang, and Sehee Hong. "A Comparison of Different Nonnormal Distributions in Growth Mixture Models." Educational and Psychological Measurement 79, no. 3 (2019): 577–97. http://dx.doi.org/10.1177/0013164418823865.

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The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew- t with equal skew and skew- t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with two different models: an unconditional GMM and a GMM with a continuous distal outcome variable. For the simulation, data were generated under the conditions of a different number of time points (4, 8), sample size (300, 800, 1,500), and skewness for
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Dissertations / Theses on the topic "Skew-t"

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Wang, Sheng. "Regularized skewness parameter estimation for multivariate skew normal and skew t distributions." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6875.

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The skewed normal (SN) distribution introduced by Azzalini has opened a new era for analyzing skewed data. The idea behind it is that it incorporates a new parameter regulating shape and skewness on the symmetric Gaussian distribution. This idea was soon extended to other symmetric distributions such as the Student's t distribution, resulting in the invention of the skew t (ST) distribution. The multivariate versions of the two distributions, i.e. the multivariate skew normal (MSN) and multivariate skew t (MST) distributions, have received considerable attention because of their ability to t s
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Zheng, Shimin, A. K. Gupta, and Xuefeng Liu. "A Matrix Variate Generalization of the Skew Pearson Type VII and Skew T Distribution." Digital Commons @ East Tennessee State University, 2012. https://dc.etsu.edu/etsu-works/74.

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Kantor, Benavides Alejandro. "Estudio de tres propuestas de distribución skew-t." Master's thesis, Pontificia Universidad Católica del Perú, 2015. http://tesis.pucp.edu.pe/repositorio/handle/123456789/6997.

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Este trabajo compara tres distribuciones skew-t. En particular, las propuestas por Branco y Dey (2001) y Azzalini y Capitanio (2003), Fernández y Steel (1998), y Jones y Faddy (2003). Se analiza la relación entre los parámetros y el nivel de asimetría a través de la medida de Patil et al. (2014). Se propone una nueva parametrización de la distribución skew-t de Jones y Faddy (2003) que modela mejor la asimetría. Las distribuciones son ajustadas a datos reales basados en el retorno logarítmico de la tasa de cambio de PEN a USD.<br>Tesis
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Muller, Fernanda Maria. "MELHORAMENTOS INFERENCIAIS NO MODELO BETA-SKEW-T-EGARCH." Universidade Federal de Santa Maria, 2016. http://repositorio.ufsm.br/handle/1/8394.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>The Beta-Skew-t-EGARCH model was recently proposed in literature to model the volatility of financial returns. The inferences over the model parameters are based on the maximum likelihood method. The maximum likelihood estimators present good asymptotic properties; however, in finite sample sizes they can be considerably biased. Monte Carlo simulations were used to evaluate the finite sample performance of point estimators. Numerical results indicated that the maximum likelihood estimators of some parameters are biased in sample si
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Garzon, Rozo Betty Johanna. "Modelling operational risk using skew t-copulas and Bayesian inference." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/25751.

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Operational risk losses are heavy tailed and are likely to be asymmetric and extremely dependent among business lines/event types. The analysis of dependence via copula models has been focussed on the bivariate case mainly. In the vast majority of instances symmetric elliptical copulas are employed to model dependence for severities. This thesis proposes a new methodology to assess, in a multivariate way, the asymmetry and extreme dependence between severities, and to calculate the capital for operational risk. This methodology simultaneously uses (i) several parametric distributions and an al
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Basalamah, Doaa. "Statistical Inference for a New Class of Skew t Distribution and Its Related Properties." Bowling Green State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1496762068499547.

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Macerau, Walkiria Maria de Oliveira. "Comparação das distribuições α-estável, normal, t de student e Laplace assimétricas". Universidade Federal de São Carlos, 2012. https://repositorio.ufscar.br/handle/ufscar/4555.

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Made available in DSpace on 2016-06-02T20:06:06Z (GMT). No. of bitstreams: 1 4185.pdf: 8236823 bytes, checksum: fc450b707396aa2c496c5373af93ef3d (MD5) Previous issue date: 2012-01-27<br>Financiadora de Estudos e Projetos<br>Abstract The asymmetric distributions has experienced great development in recent times. They are used in modeling financial data, medical, genetics and other applications. Among these distributions, the Skew normal (Azzalini, 1985) has received more attention from researchers (Genton et al., (2001), Gupta et al., (2004) and Arellano-Valle et al., (2005)). We present a
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Lengua, Lafosse Patricia. "An empirical application of stochastic volatility models to Latin-American stock returns using GH skew student's t-distribution." Master's thesis, Pontificia Universidad Católica del Perú, 2015. http://tesis.pucp.edu.pe/repositorio/handle/123456789/6167.

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This paper represents empirical studies of stochastic volatility (SV) models for daily stocks returns data of a set of Latin American countries (Argentina, Brazil, Chile, Mexico and Peru) for the sample period 1996:01-2013:12. We estimate SV models incorporating both leverage effects and skewed heavy-tailed disturbances taking into account the GH Skew Student’s t-distribution using the Bayesian estimation method proposed by Nakajima and Omori (2012). A model comparison between the competing SV models with symmetric Student´s t-disturbances is provided using the log marginal likelihoods in the
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Hasan, Abeer. "A Study of non-central Skew t Distributions and their Applications in Data Analysis and Change Point Detection." Bowling Green State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1371055538.

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Coelho, Carina Figueiredo. "Misturas finitas de normais assimétricas e de t assimétricas aplicadas em análise discriminante." Universidade Federal do Amazonas, 2013. http://tede.ufam.edu.br/handle/tede/4244.

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Submitted by Kamila Costa (kamilavasconceloscosta@gmail.com) on 2015-06-18T20:16:38Z No. of bitstreams: 1 Dissertação-Carina Figueiredo Coelho.pdf: 3096964 bytes, checksum: 57c06ccd1fdc732a7cf9a50381d3806b (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-06T15:29:34Z (GMT) No. of bitstreams: 1 Dissertação-Carina Figueiredo Coelho.pdf: 3096964 bytes, checksum: 57c06ccd1fdc732a7cf9a50381d3806b (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-06T15:27:26
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Books on the topic "Skew-t"

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Cheng, Russell. The Skew Normal Distribution. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0012.

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This chapter considers the univariate skew-normal distribution, a generalization of the normal that includes the normal as a special case. The most natural parametrization is non-standard. This is because the Fisher information matrix is then singular at the true parameter value when the true model is the normal special case. The log-likelihood is then particularly flat in a certain coordinate direction. Standard theory cannot then be used to calculate the asymptotic distribution of all the parameter estimates. This problem can be handled using an alternative parametrization. There is another
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Book chapters on the topic "Skew-t"

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Yeap, Claudia, S. T. Boris Choy, and S. Simon Kwok. "The Skew-t Option Pricing Model." In Econometrics for Financial Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73150-6_25.

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Lee, Sharon X., and Geoffrey J. McLachlan. "Risk Measures Based on Multivariate Skew Normal and Skew t-Mixture Models." In Asymmetric Dependence in Finance. John Wiley & Sons Ltd, 2018. http://dx.doi.org/10.1002/9781119288992.ch7.

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Kollo, Tõnu, and Gaida Pettere. "Parameter Estimation and Application of the Multivariate Skew t-Copula." In Copula Theory and Its Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12465-5_15.

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Gavet, Yann, Ola Suleiman Ahmad, and Jean-Charles Pinoli. "Integral Geometry of Linearly Combined Gaussian and Student-t, and Skew Student’s t Random Fields." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40020-9_49.

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Azzalini, Adelchi. "Flexible Distributions as an Approach to Robustness: The Skew-t Case." In Recent Advances in Robust Statistics: Theory and Applications. Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-3643-6_1.

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Azzalini, Adelchi, and Mahdi Salehi. "Some Computational Aspects of Maximum Likelihood Estimation of the Skew-t Distribution." In Emerging Topics in Statistics and Biostatistics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42196-0_1.

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Lee, Sharon X., and Geoffrey J. McLachlan. "Unsupervised Component-Wise EM Learning for Finite Mixtures of Skew t-distributions." In Advanced Data Mining and Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49586-6_49.

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Güney, Yeşim, Olcay Arslan, and Hamparsum Bozdogan. "Variable Selection in Heteroscedastic Regression Models Under General Skew-t Distributional Models Using Information Complexity." In Emerging Topics in Statistics and Biostatistics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42196-0_4.

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Sadeghkhani, Abdolnasser, and Syed Ejaz Ahmed. "Bayesian Predictive Densities as an Interpretation of a Class of Skew–Student t Distributions with Application to Medical Data." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21248-3_31.

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Berk, Maurice, and Giovanni Montana. "A Skew-t-Normal Multi-level Reduced-Rank Functional PCA Model for the Analysis of Replicated Genomics Time Course Data." In Advances in Intelligent Data Analysis XI. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34156-4_7.

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Conference papers on the topic "Skew-t"

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Muller, Philipp, and Robert Piche. "Statistical trilateration with skew-t errors." In 2015 International Conference on Localization and GNSS (ICL-GNSS). IEEE, 2015. http://dx.doi.org/10.1109/icl-gnss.2015.7217164.

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Zhou, Rui, and Daniel P. Palomar. "Accelerating the Multivariate SKEW T Parameter Estimation." In 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2019. http://dx.doi.org/10.1109/camsap45676.2019.9022437.

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"MAXIMUM LIKELIHOOD ESTIMATION OF MULTIVARIATE SKEW T-DISTRIBUTION." In 1st International Conference on Operations Research and Enterprise Systems. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003727002000203.

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Vaiciulyte, Ingrida. "Adaptive Monte-Carlo Markov chain for multivariate statistical estimation." In International Workshop of "Stochastic Programming for Implementation and Advanced Applications". The Association of Lithuanian Serials, 2012. http://dx.doi.org/10.5200/stoprog.2012.21.

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The estimation of the multivariate skew t-distribution by the Monte-Carlo Markov Chain (MCMC) method is considered in the paper. Thus, the MCMC procedure is constructed for recurrent estimation of skew t-distribution, following the maximum likelihood method, where the Monte-Carlo sample size is regulated to ensure the convergence and to decrease the total amount of Monte-Carlo trials, required for estimation. The confidence intervals of Monte-Carlo estimators are introduced because of their asymptotic normality. The termination rule is also implemented by testing statistical hypotheses on an i
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Li, Shuhui, Zhihong Deng, Ruxuan He, Feng Pan, Xiaoxue Feng, and Ni Pu. "Robust Variational Bayesian Filter for Systems with Skew t Noise." In 2020 Chinese Automation Congress (CAC). IEEE, 2020. http://dx.doi.org/10.1109/cac51589.2020.9327529.

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Yan, Xin, Laurent Clavier, Gareth W. Peters, Nourddine Azzaoui, Francois Septier та Ido Nevat. "Skew-t copula for dependence modelling of impulsive (α-stable) interference". У 2015 IEEE International Conference on Signal Processing for Communications (ICC). IEEE, 2015. http://dx.doi.org/10.1109/icc.2015.7249085.

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Wang, Zongyuan, Weidong Zhou, Ling Xue, Huanzhang Ling, and Tao Chen. "An EKF algorithm based on a skew-t measurement noise model." In 2017 36th Chinese Control Conference (CCC). IEEE, 2017. http://dx.doi.org/10.23919/chicc.2017.8028161.

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Wang, Kui, Shu-Kay Ng, and Geoffrey J. McLachlan. "Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data." In 2009 Digital Image Computing: Techniques and Applications. IEEE, 2009. http://dx.doi.org/10.1109/dicta.2009.88.

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Ahmad, Ola Suleiman, and Jean-Charles Pinoli. "Lipschitz-Killing Curvatures of the Excursion Sets of Skew Student-t Random Fields." In 2nd Annual International Conference on Computational Mathematics, Computational Geometry & Statistics. Global Science Technology Forum, 2013. http://dx.doi.org/10.5176/2251-1911_cmcgs13.05.

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Wei, Wang. "Interacting Multiple Model Algorithm Using Skew-t Measurement Noise and Variational Bayesian Approach." In 2018 37th Chinese Control Conference (CCC). IEEE, 2018. http://dx.doi.org/10.23919/chicc.2018.8482655.

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