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Dissertations / Theses on the topic 'AR(1) model'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 January 2023

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1

Rastenė, Irma. "Testing and estimating changed segment in autoregressive model." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20110628_134429-88914.

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In the doctoral dissertation, we consider problems of testing and estimating changed segment with unknown starting position and duration of epidemic state in the autoregressive first-order model. The proposed tests are based on partial sums of model residuals and model-parameter partial-estimator polygonal line processes. We derive asymptotic results for these processes in Holder spaces. The behavior of test statistics under the null hypothesis of no change and alternative is provided. Empirical power analysis has shown that tests are more powerful when absolute values of model parameter are q

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2

Morais, Telma Suely da Silva. "Abordagem Bayesiana do modelo AR(1) para dados em painel: uma aplicação em dados temporais de microarray." Universidade Federal de Viçosa, 2008. http://locus.ufv.br/handle/123456789/4016.

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Made available in DSpace on 2015-03-26T13:32:05Z (GMT). No. of bitstreams: 1 texto completo.pdf: 717763 bytes, checksum: e623d83648529a004b8aa2a3e4877433 (MD5) Previous issue date: 2008-12-05<br>We considered a Bayesian analysis of first order autoregressive, AR(1), panel data model, using exact likelihood function, comparative analysis of prior distributions and predictive distributions of future observations. The methodology efficiency was evaluated by a simulation study using three prior, which were related to different Generalized Beta distributions: symmetric, asymmetric and flat prior.

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3

Rastenė, Irma. "Autoregresinio modelio pasikeitusio segmento testavimas ir vertinimas." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20110628_134442-76842.

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Disertacijoje nagrinėjamas pirmos eilės autoregresinio modelio pasikeitusio segmento testavimo ir vertinimo uždavinys. Aprašomo modelio epideminio pasikeitimo pradžia ir ilgis nėra žinomi. Pasiūlyti kriterijai pasikeitusio segmento testavimui, kurie pagrįsti modelio paklaidų įvertinių dalinių sumų ir modelio parametro dalinių įvertinių laužčių procesais. Šiems procesams gautos ribinės teoremos Hiolderio erdvėse. Nurodomas testų statistikų ribinis elgesys esant teisingai nulinei ir alternatyviajai hipotezėms. Iš empirinio kriterijų galios tyrimo rezultatų matyti, kad pasiūlytų testų galia didži

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4

Quiner, Trevor Elisha. "Chemopreventive Effects of Dietary Selenium and Soy Isoflavones in a Mouse Model of Prostate Cancer." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2541.

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Prostate cancer is the most commonly diagnosed non-skin cancer in men and the second leading cause of cancer death in the United States. Prostate cancer, like many cancers, is a disease that generally requires a long period of time to develop and grow before it becomes detectable. This long period of latency makes prostate cancer a candidate for dietary chemoprevention. Soy and selenium (Se), are associated with a decreased risk of prostate cancer. We previously showed that high dietary intake of selenium (Se) and soy isoflavones decreased the expression of the androgen receptor (AR) and AR-re

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5

Richmann, Michael K. "Comparison of mechanistic model with experimental observation : Part 1. The Ar(2p?) [to] Ar(1s?) emission signal in the pulse radiolysis of argon. Part 2. An absorption study of the argon 1s species /." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487759055158801.

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6

Yucer, Cem Tahsin. "Modelling The Evolution Of Demand Forecasts In A Production-distribution System." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12608109/index.pdf.

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In this thesis, we focus on a forecasting tool, Martingale Model of Forecast Evolution (MMFE), to model the evolution of forecasts in a production-distribution system. Additive form is performed to represent the evolution process. Variance-Covariance (VCV) matrix is defined to express the forecast updates. The selected demand pattern is stationary and it is normally distributed. It follows an Autoregressive Order-1 (AR(1)) model. Two forecasting procedures are selected to compare the MMFE with. These are MA (Moving average) and ES (Exponential smoothing) methods. A production-distribution mode

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7

Moser, Mathias, and Klara Zwickl. "Informal environmental regulation of industrial air pollution: Does neighborhood inequality matter?" WU Vienna University of Economics and Business, 2014. http://epub.wu.ac.at/4350/1/wp192.pdf.

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This paper analyzes if neighborhood income inequality has an effect on informal regulation of environmental quality, using census tract-level data on industrial air pollution exposure from EPA´s Risk Screening Environmental Indicators and income and demographic variables from the American Community Survey and EPA´s Smart Location Database. Estimating a spatial lag model and controlling for formal regulation at the states level, we find evidence that overall neighborhood inequality - as measured by the ratio between the fourth and the second income quintile or the neighborhood Gini coefficient

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Acosta, Argueta Lesly María. "Particle filtering estimation for linear and nonlinear state-space models." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/134356.

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The sequential estimation of the states (filtering) and the corresponding simultaneous estimation of the states and fixed parameters of a dynamic state-space model, being linear or not, is an important probleminmany fields of research, such as in the area of finance. The main objective of this research is to estimate sequ entially and efficiently –from a Bayesian perspective via the particle filtering methodology– the states and/or the fixed parameters of a nonstandard dynamic state-spacemodel: one that is possibly nonlinear, non-stationary or non-Gaussian. The present thesis consists of sev

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9

Yi, Qilong. "Random effects and AR(1) models in longitudinal data analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ49731.pdf.

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Tibulo, Cleiton. "MODELOS DE SÉRIES TEMPORAIS APLICADOS A DADOS DE UMIDADE RELATIVA DO AR." Universidade Federal de Santa Maria, 2014. http://repositorio.ufsm.br/handle/1/8334.

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Time series model have been used in many areas of knowledge and have become a current necessity for companies to survive in a globalized and competitive market, as well as climatic factors that have always been a concern because of the different ways they interfere in human life. In this context, this work aims to present a comparison among the performances by the following models of time series: ARIMA, ARMAX and Exponential Smoothing, adjusted to air relative humidity (UR) and also to verify the volatility present in the series through non-linear models ARCH/GARCH, adjusted to residues of the

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11

PEDRUZZI, R. "AVALIAÇÃO DE DESEMPENHO DO MODELO FOTOQUÍMICO CMAQ UTILIZANDO DIFERENTES CONDIÇÕES DE CONTORNO EM UMA REGIÃO URBANA E INDUSTRIALIZADA." Universidade Federal do Espírito Santo, 2016. http://repositorio.ufes.br/handle/10/10317.

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Made available in DSpace on 2018-08-24T22:53:40Z (GMT). No. of bitstreams: 1 tese_9973_dissertacao-Rizzieri-Condicoes_Contorno_CMAQ_CORRECAO-rev-final.pdf: 10549247 bytes, checksum: eeb5475c2c5fe4865a8e58836416877c (MD5) Previous issue date: 2016-04-13<br>O objetivo principal deste trabalho foi avaliar a influência das condições de contorno nas simulações com o modelo CMAQ sobre a Região Metropolitana da Grande Vitória (RMGV) para os poluentes, ozônio (O3) e material particulado inalável (MP10). Foram feitos quatro cenários de simulação para o mês de agosto de 2010 com diferentes condições d

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Kamanu, Timothy Kevin Kuria. "Location-based estimation of the autoregressive coefficient in ARX(1) models." Thesis, University of the Western Cape, 2006. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_9551_1186751947.

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<p>In recent years, two estimators have been proposed to correct the bias exhibited by the leastsquares (LS) estimator of the lagged dependent variable (LDV) coefficient in dynamic regression models when the sample is finite. They have been termed as &lsquo<br>mean-unbiased&rsquo<br>and &lsquo<br>medianunbiased&rsquo<br>estimators. Relative to other similar procedures in the literature, the two locationbased estimators have the advantage that they offer an exact and uniform methodology for LS estimation of the LDV coefficient in a first order autoregressive model with or without exogenous regr

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13

Couto, Vanessa Barcelos. "Fluxos de amônia e óxido nitroso na interface ar-água do sistema lagunar de Maricá-Guarapina." Niterói, 2017. https://app.uff.br/riuff/handle/1/3604.

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Submitted by Biblioteca de Pós-Graduação em Geoquímica BGQ (bgq@ndc.uff.br) on 2017-05-16T17:00:09Z No. of bitstreams: 1 Microsoft Word - Vanessa Dissertaçao.pdf: 1678884 bytes, checksum: ee88f8d0505bb8844a68dc56e1473779 (MD5)<br>Made available in DSpace on 2017-05-16T17:00:09Z (GMT). No. of bitstreams: 1 Microsoft Word - Vanessa Dissertaçao.pdf: 1678884 bytes, checksum: ee88f8d0505bb8844a68dc56e1473779 (MD5)<br>Universidade Federal Fluminense. Instituto de Química. Programa de Pós-Graduação em Geoquímica, Niterói, RJ<br>Este estudo analisa os fluxos de óxido nitroso (N 2 O) e amôn

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14

Pilipauskaité, Vytauté. "Limit theorems for spatio-temporal models with long-range dependence." Thesis, Nantes, 2017. http://www.theses.fr/2017NANT4057/document.

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Les travaux de la thèse portent sur les théorèmes limites pour des modèles stochastiques à forte dépendance. Dans la première partie, nous considérons des modèles AR(1) à coefficient aléatoire. Nous identifions trois régimes asymptotiques différents pour le schéma d’agrégation conjointe temporelle-contemporaine lorsque les processus AR sont indépendants et lorsque les AR possède des innovations communes. Ensuite, on discute de l’estimation non paramétrique de la fonction de répartition du coefficient autorégressif à partir d’un panel de séries AR(1) à coefficient aléatoire. Nous prouvons la co

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15

Rodrigues, Juliana Pilato. "Modelagem matemática da dispersão de poluentes atmosféricos como etapa de pré-seleção de locais para instalação de estações de monitoramento da qualidade do ar em Paranaguá - PR." Universidade Tecnológica Federal do Paraná, 2016. http://repositorio.utfpr.edu.br/jspui/handle/1/1850.

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CAPES<br>Este estudo teve por objetivo sugerir locais para o monitoramento da qualidade do ar no município de Paranaguá-PR. Para tal, foi utilizada modelagem matemática de dispersão de poluentes atmosféricos, associada ao levantamento de informações sobre adensamento populacional e distribuição de equipamentos urbanos nos bairros do município. Com o uso do software de modelagem AERMOD foram simuladas as concentrações de CO, NOX, SO2, PTS e HCT, considerando emissão veicular, industrial e do Porto de Paranaguá. Os dados meteorológicos utilizados nas simulações consistiram em uma série horária d

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16

Leoni, Roberto Campos [UNESP]. "Estudo do desempenho dos gráficos de controle quando a média do processo oscila de acordo com o modelo AR(1)." Universidade Estadual Paulista (UNESP), 2011. http://hdl.handle.net/11449/93086.

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Made available in DSpace on 2014-06-11T19:26:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-06-15Bitstream added on 2014-06-13T20:15:05Z : No. of bitstreams: 1 leoni_rc_me_guara.pdf: 1800797 bytes, checksum: 8d64168d2cc2cc40045086a8c4677b9f (MD5)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>No planejamento dos gráficos de controle destinados ao monitoramento da média do processo, assume-se que esta permanece fixa em seu valor alvo até a ocorrência de uma causa especial, que a desloca. Em muitos processos, contudo, é mais razoável supor que a média osci

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17

Leoni, Roberto Campos. "Estudo do desempenho dos gráficos de controle quando a média do processo oscila de acordo com o modelo AR(1) /." Guaratinguetá : [s.n.], 2011. http://hdl.handle.net/11449/93086.

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Resumo: No planejamento dos gráficos de controle destinados ao monitoramento da média do processo, assume-se que esta permanece fixa em seu valor alvo até a ocorrência de uma causa especial, que a desloca. Em muitos processos, contudo, é mais razoável supor que a média oscila mesmo na ausência de causas especiais. Para descrever este comportamento oscilatório, tem-se utilizado o modelo autoregressivo de 1ª ordem, AR (1). Quando esta oscilação é grande, o melhor desempenho do gráfico de X é obtido com amostras unitárias. O mesmo não se observa com a carta de EWMA (exceto quando o parâmetro de p

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18

Cavalli, Jean Pierre. "Produtividade de Eucalyptus saligna com base nas propriedades físico-hídricas do solo e parametrização do modelo ecofisiológico 3-pg." Universidade Federal de Santa Maria, 2017. http://repositorio.ufsm.br/handle/1/13332.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>This study was developed in Serra do Sudeste and Encosta do Sudeste physiographic regions of Rio Grande do Sul state. The objective was to identify the physical and hydraulic soil properties related to forest yield sites in two distinct areas, including physical-structural properties and soil available water capacity (AW) of Argissolo Vermelho-Amarelo Distrófico típico, Argissolo Vermelho-Amarelo Distrófico latossólico (ARG) and Neossolo Quartzarênico Órtico típico (NEO), as well as perform parameterization of the Physiolog

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Sandi, Nathanyel. "Modelagem e análise de topologias para veículos aéreos não-tripulados do tipo multirotor." Universidade Tecnológica Federal do Paraná, 2017. http://repositorio.utfpr.edu.br/jspui/handle/1/2817.

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Com a evolução dos projetos de multirotores e dos seus componentes, os projetistas vem tendo inúmeras opções de combinações de componentes na fase de projeto do multirotor, buscando melhor performance e menor custo. Isto deixa um problema em aberto: como atingir o multirotor pode atingir uma boa performance ainda na fase de projeto. A motivação para realização deste estudo se justifica no fato que não há trabalhos relacionado ao levantamento de métricas e análise de performance dos multirotores. Assim como o fator de não haver formas de mensurar a qualidade dos projetos e ter possibilidade de

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20

Purutcuoglu, Vilda. "Unit Root Problems In Time Series Analysis." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12604701/index.pdf.

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In time series models, autoregressive processes are one of the most popular stochastic processes, which are stationary under certain conditions. In this study we consider nonstationary autoregressive models of order one, which have iid random errors. One of the important nonstationary time series models is the unit root process in AR (1), which simply implies that a shock to the system has permanent effect through time. Therefore, testing unit root is a very important problem. However, under nonstationarity, any estimator of the autoregressive coefficient does not have a known exact distribut

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21

Hledík, Jakub. "Binomický autoregresní model." Master's thesis, 2021. http://www.nusl.cz/ntk/nusl-437942.

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Binomial AR(1) process is a model for integer-valued time series with a fi- nite range and discrete time. It has the binomial marginal distribution and the AR(1)-like autocorrelation structure. This thesis deals with deriving some ba- sic properties of this process, methods of parameter estimation and goodness of fit testing. Three methods of parameter estimation are presented: Yule-Walker, the conditional least squares and the maximum likelihood method together with proofs of their asymptotical properties. Next, the goodness of fit testing is pre- sented. At first, two known methods based on

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22

Lin, Hsiao-chi, and 林曉祺. "Optimal Portfolio Selection with Spectral Risk Measure under AR(1)-Copula Model." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/2j39e2.

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碩士<br>國立高雄大學<br>統計學研究所<br>101<br>In this article, a portfolio selection problem with spectral risk measure is considered. The dynamics of the returns of each underlying asset is modeled by an autoregressive model of order 1. The tail dependence structure of the underlying asset-return vector is depicted by a copula function. The technique of linear programming is employed to solve the optimal asset allocation. Empirical studies are conducted for investigating the impact of the degree of risk aversion, the level of autocorrelation and the tail dependence for underlying assets on the portfolio s

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23

Peng, Feng-Yang, and 彭豐洋. "Linear Trimmed Means for the Linear Regression with AR(1) Errors Model." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/02929730829547493450.

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碩士<br>國立交通大學<br>統計學研究所<br>93<br>For the linear regression with AR(1) errors model, a robust type generalized and feasible generalized estimators of Lai et al. (2003) of regression parameters are shown to have the desired property of robust type Gauss Markov theorem. It is done by shown that these two estimators are, respectively, the best among classes of linear trimmed means. Monte Carlo and data analysis for this technique have been performed.

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Hu, Hsu-Ning, and 胡緒寧. "The Relative Price Between Index Spot And Index Futures Using MS-AR(1) Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/jsgk6v.

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碩士<br>淡江大學<br>財務金融學系碩士在職專班<br>95<br>Because of the high liquidity and lower fee, the index futures become the favorable tools for the purpose of hedging, arbitraging and speculating. In this paper, we use the weekly data of spot price and futures price from the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the MSCI Taiwan Index to investigate the behavior of the relative price between the spot and futures. We also check the relationship between the volatility of return of both spot and futures and the relative price. The empirical results indicated that : (1) Both relat

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25

Liu, Kuo-Ching, and 柳國清. "Bayesian Analysis of a General Growth Curve Model with Power Transformations and AR(1) Dependence." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/27357607352519403459.

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碩士<br>國立交通大學<br>統計學研究所<br>83<br>In this paper we consider Bayesian analysis of the unbalanced (general) growth curve model with AR(1) dependence, while applying the Box-Cox power transformations. We propose both parameter estimation and prediction of future values. Meanwhile, Bayesian inference by means of Gibbs sampling is also studied. Numerical results are illustrated with several sets of real and simulated data.

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Lien, Wen-Huey, and 連文惠. "Bayesian Analysis of a Growth Curve Model with Power Transformation, Random Effects and AR(1) Dependence." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/43729700919066095703.

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碩士<br>國立交通大學<br>統計學類<br>86<br>In this paper we devote ourselves to a general growth curve modelwith power transformation, random effects and AR(1) dependence via aBayesian approach. Two priors are proposed and both parameters estimationand prediction of future values are considered. Some numerical resultswith a set of real data are also given.

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HUANG, ZHEN-YUAN, and 黃振原. "The limiting distributions of the least square estimate of the AR(1) model with long-memory errors." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/45135505616007849679.

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Thyer, Mark Andrew. "Modelling Long-Term Persistence in Hydrological Time Series." Thesis, 2001. http://hdl.handle.net/1959.13/24891.

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The hidden state Markov (HSM) model is introduced as a new conceptual framework for modelling long-term persistence in hydrological time series. Unlike the stochastic models currently used, the conceptual basis of the HSM model can be related to the physical processes that influence long-term hydrological time series in the Australian climatic regime. A Bayesian approach was used for model calibration. This enabled rigourous evaluation of parameter uncertainty, which proved crucial for the interpretation of the results. Applying the single site HSM model to rainfall data from selected Australi

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Thyer, Mark Andrew. "Modelling Long-Term Persistence in Hydrological Time Series." 2001. http://hdl.handle.net/1959.13/24891.

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The hidden state Markov (HSM) model is introduced as a new conceptual framework for modelling long-term persistence in hydrological time series. Unlike the stochastic models currently used, the conceptual basis of the HSM model can be related to the physical processes that influence long-term hydrological time series in the Australian climatic regime. A Bayesian approach was used for model calibration. This enabled rigourous evaluation of parameter uncertainty, which proved crucial for the interpretation of the results. Applying the single site HSM model to rainfall data from selected Australi

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Wu, Hsin-Lun, and 吳欣倫. "Bayesian Analysis of AR(1) Models." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/rauc5u.

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碩士<br>銘傳大學<br>應用統計資訊學系碩士班<br>93<br>We study the Bayesian analysis of AR(1) models. The priors discussed by James O. Berger & Ruo-Yong Yang (1994) and Domenico Marinucci & Lea Petrella (1999) are compared along with a new one which seems more appealing to us. Two criteria are used for the evaluation of the performance of the priors, i.e., the posterior mean square error (MSE) and frequentist coverage probability based on posterior quantiles. Our simulated results are in very close agreement with the results by James O. Berger & Ruo-Yong Yang (1994) and Marinucci & Lea Petrella (1999) for the pr

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31

Onderko, Martin. "Autoregresní modely typu NIAR(1)." Master's thesis, 2015. http://www.nusl.cz/ntk/nusl-336697.

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My final thesis firstly addresses basic knowledge of the theory of stochastic processes. This is firstly due to the author's effort to make the thesis more comprehensible, and also due to the need for introduction of key concepts. The autoregressive model AR(1) is defined in the thesis through basic linear time series models, and in this model, the estimation of model parameter by the method of least squares is introduced. For this estimation, the theoretical findings of the thesis are extended through the classical limit theory. Furthermore, the models with their parameter dependent on number

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32

Niu, Wei-Fang, and 牛維方. "Bayesian Analysis of Models for Longitudinal Data with Random Effects and AR(1) Errors." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/67374012302472019494.

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碩士<br>國立交通大學<br>統計學研究所<br>84<br>In this paper we consider a Bayesian analysis of unbalanced (general) growth curve model with random effects and AR(1) errors. Three priors are proposed and put into comparisons in parameter estimation and prediction problems.

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Zhu, Rong. "On continuous-time generalized AR(1) processes : models, statistical inference, and applications to non-normal time series." Thesis, 2002. http://hdl.handle.net/2429/13317.

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This thesis develops the theory of continuous-time generalized AR(1) processes and presents their use for non-normal time series models. The theory is of dual interest in probability and statistics. From the probabilistic viewpoint, this study generalizes a type of Markov process which has a similar representation structure to the Ornstein-Uhlenbeck process (or continuous-time Gaussian AR(1) process). However, the stationary distributions can now have support on non-negative integers, or positive reals, or reals; the dependence structures are no longer restricted to be linear. From the s

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