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weightedScores (version 0.9.5.3)

Weighted Scores Method for Regression Models with Dependent Data

Description

The weighted scores method and composite likelihood information criteria as an intermediate step for variable/correlation selection for longitudinal ordinal and count data in Nikoloulopoulos, Joe and Chaganty (2011) , Nikoloulopoulos (2016) and Nikoloulopoulos (2017) .

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Version

Install

install.packages('weightedScores')

Monthly Downloads

250

Version

0.9.5.3

License

GPL (>= 2)

Maintainer

Aristidis Nikoloulopoulos

Last Published

March 23rd, 2020

Functions in weightedScores (0.9.5.3)

NEGATIVE LOG-LIKELIHOOD ASSUMING INDEPEDENCE WITHIN CLUSTERS

INDEPENDENT ESTIMATING EQUATIONS FOR BINARY AND COUNT REGRESSION

WEIGHT MATRICES FOR THE ESTIMATING EQUATIONS

APPROXIMATION OF BIVARIATE STANDARD NORMAL DISTRIBUTION

Maximum Likelihood for Ordinal Model

CL1 INFORMATION CRITERIA

OPTIMIZATION ROUTINE FOR BIVARIATE COMPOSITE LIKELIHOOD FOR MVN COPULA

INVERSE GODAMBE MATRIX

COVARIANCE MATRIX OF THE UNIVARIATE SCORES

SOLVING THE WEIGHTED SCORES EQUATIONS WITH INPUTS OF THE WEIGHT MATRICES AND THE DATA

BIVARIATE COMPOSITE LIKELIHOOD FOR MULTIVARIATE NORMAL COPULA WITH CATEGORICAL AND COUNT REGRESSION

Hospital Visit Data

The toenail infection data

MVN Rectangle Probabilities

THE WEIGHTED SCORES EQUATIONS WITH INPUTS OF THE WEIGHT MATRICES AND THE DATA

Rheumatoid Arthritis Clinical Trial

weightedScores-package

Weighted Scores Method for Regression Models with Dependent Data

DENSITY AND CDF OF THE UNIVARIATE MARGINAL DISTRIBUTION

Derivatives of Multivariate Normal Rectangle Probabilities

THE WEIGHTED SCORES METHOD WITH INPUTS OF THE DATA