A multivariate generalized Poisson regression model based on the multivariate generalized Poisson distribution is defined and studied. The regression model can be used to describe a count data with any type of dispersion. The model allows for both positive and negative correlation between any pair of...
内容提示: Ma, Kockelman & Damien 1 A Multivariate Poisson-Lognormal Regression Model for Prediction of Crash Counts by Severity, using Bayesian Methods Jianming Ma, Ph.D., The University of Texas at Austin. 6.9 E. Cockrell Jr. Hall, Austin, TX 78712-1076, mjming@mail.utexas.edu Kara M...
In a multivariate "errors in variables" regression model, the unknown mean vectors $\\mathbf{u}_{1i}: p imes 1, \\mathbf{u}_{2i}: r imes 1$ of the vector observations $\\mathbf{x}_{1i}, \\mathbf{x}_{2i}$, rather than the observations themselves, are assumed to follow the...
This paper presents emission factors of a class of passenger cars obtained by applying a statistical model developed to evaluate average emission factors based on driving cycle emission measurements. A multivariate regression method based on principal components, namely, the partial least squares (PLS) ...
measure (e.g. a Wald test statistic or a likelihood ratio test). Only the top ranking features (i.e. features with the most significant univariate significance levels) will become candidate covariates for forward selection in a multivariate regression model. The top number of candidate features ...
In this paper, a method of building multivariate threshold regression model is given. The idea is mainly based on the fact that the relation between predictor and predictand will change when some spe-cial predictors change abruptly. Computational results
A Multivariate Poisson-Lognormal Regression Model for Prediction of Crash Counts by Severit Numerous efforts have been devoted to investigating crash occurrence as related to roadway design features, environmental and traffic conditions. However, most of the research has relied on univariate count model....
Using the multivariate multilevel logistic regression model to detect DIF: A comparison with HGLM and logistic regression DIF detection methods This study presents the Multivariate Multilevel Logistic Regression (MMLR) models to detect Differential Item Functioning (DIF), which are likely to detect.....
We use a multivariate regression model (1) where Y i is the expression of gene i, S ij is the score of the j th TF on gene i, w j is the regression coefficient of the j th TF, and e i is the error term. The score S ij is given by (2) where g k is the perk inten...
Multivariate Behav Res. 2012;47(5):667–96. https://doi.org/10.1080/00273171.2012.715555. Article PubMed PubMed Central Google Scholar Ou XC. Multidimensional structure or wording effect? Reexamination of the factor structure of the Chinese General Self-Efficacy Scale. J Pers Assess. 2022;...