Dissertation > Excellent graduate degree dissertation topics show
The Extensions of Two Multivariate Statistical Models and the Local Influence
Author: JiangJie
Tutor: LiuXinSheng
School: Nanjing University of Aeronautics and Astronautics
Course: Computational Mathematics
Keywords: Multinomial probit model local influence analysis conformal normal curvature multivariate probit model EM algotithm MCEM algorithm MCECM algorithm
CLC: O212.4
Type: Master's thesis
Year: 2009
Downloads: 37
Quote: 0
Read: Download Dissertation
Abstract
Multinomial probit and multivariate probit model are two important statistical models that have been applied in many fields, such as in econometrics, biostatistics, transportaion studies, psychics, medicine and behavior science. In the past decades, many authors have studied the two models, and made them advanced. For example, MNPFA and MPCFA models were extended models by incorporating factor analysis.This paper is devoted to extending the two multivariate statistical models and implementing local influence analysis of them, and the EM algorithm is used to estimate parameters of the two models based on maximum likelihood estimates. In chapter 2, we consider local influence analysis, which is wellrecognized important step of data analysis, of MNPFA model based on the theory of statistical diagnosis. Then we can obtain assessment of local influence in minor perturbations of the statistical model. The assessment of local influence of MNPFA models is illustrated by numerical simulations, and the results show that the proposed method is feasible and stable. For fitting samples with long tails, in chapter 3 we extend MNPFA model by assuming tdistribution error in probit factor analysis. The MCECM algorithm is used to estimate parameters of the proposed models. The methodology is illustrated with numerical simulations. In chapter 4, we propose MPCFA with tdistribution error and make MPCFA model applied more widely.

Related Dissertations
 Semiparametric analysis of longitudinal ZeroInflated Count Data,O211.67
 The Extensions of Three Multivariate Statistical Models and the EM Algorithm,O212
 The Development and Evolvement of Probit Model,O212
 Based on statistics of the lognormal distribution heteroscedasticity model inferred,O212.1
 Prediction of the Longterm and Mediumterm Development Trends of Shanxi Population,O212.1
 The Research about Influencing Factors of Using Estimation Formula to Estimate Variance Compoents under Sparse Data Matrix,O212.1
 Bayesian methods under two ordinal value of multivalue data model with simultaneous identification of outliers,O212.1
 Discussion on a New Test of Conventional Asymptotics in GMM,O212.1
 Data Analysis of Multiple Repeated Measures of Childrenâ€™s Behavior,O212.1
 Counting interval mapping of quantitative trait,O212.7
 A Nonparametric Bayesian Method to Estimate Ordered Probit Model,O212.8
 Test Whether the Two Population Covariance Matrices Are Proportional,O212.1
 Multiple regression models, variable selection problem,O212.1
 Comparative Study on Economic Development of City Circle Based on Data Mining,O212.1
 Based on empirical likelihood of p order autoregressive model diagnostic statistics,O212.1
 The Bayesian Estimation of Inverse Gaussion Distribution Parameter,O212.8
 Research on the Admissible Quadratic Error Variance Estimations in Growth Curve Model, and on the Admissibility of Quadratic Estimations with Restricted Parameter Sets,O212.1
 The Parameter Estimation of Linear Mixed Model,O212.1
 On the Asymptotics of Bootstrap Test for AR(p) Unit Roots,O212.1
 Some Researches on the Ridge Estimator,O212.1
 Some Researches on Linear Regression Analysis,O212.1
CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Mathematical Statistics > Multivariate analysis
© 2012 www.DissertationTopic.Net Mobile
