
MIM
 Referenced in 134 articles
[sw26139]
 describe particular families of models, including loglinear models, Gaussian models, and models for mixed...

PROC GENMOD
 Referenced in 33 articles
[sw11741]
 linear models with normal errors, logistic and probit models for binary data, and loglinear...

glmmAK
 Referenced in 26 articles
[sw13218]
 Package glmmAK: Generalized Linear Mixed Models. This package implements maximumlikelihood estimation in the logistic ... model), and in the Poisson regression (loglinear model). Secondly, Bayesian estimation based on MCMC...

nnet
 Referenced in 16 articles
[sw07922]
 Feedforward Neural Networks and Multinomial LogLinear Models. Software for feedforward neural networks ... single hidden layer, and for multinomial loglinear models...

Uhlig Toolkit
 Referenced in 49 articles
[sw15482]
 dynamic discretetime stochastic models easily, building on loglinearizing the necessary equations characterizing...

gRbase
 Referenced in 13 articles
[sw10198]
 datasets used in the book Graphical Models with R (2012) are contained in gRbase. gRbase ... conditional independence. gRbase illustrates how hierarchical loglinear models (hllm) may be implemented and describes...

CONTRAfold
 Referenced in 8 articles
[sw17117]
 structure prediction method based on conditional loglinear models (CLLMs), a flexible class of probabilistic...

PROC CATMOD
 Referenced in 4 articles
[sw12082]
 used for linear modeling, loglinear modeling, logistic regression, and repeated measurement analysis. PROC CATMOD ... likelihood (ML) estimation of parameters for loglinear models and the analysis of generalized logits...

exactLoglinTest
 Referenced in 3 articles
[sw25926]
 Exact Hypothesis Tests for Loglinear Models with exactLoglinTest. This manuscript overviews exact testing ... linear models using the R package exactLoglinTest. This package evaluates model fit for Poisson log ... linear models by conditioning on minimal sufficient statistics to remove nuisance parameters. A Monte Carlo ... also be viewed as conditional Poisson loglinear models and hence can be performed...

gllm
 Referenced in 3 articles
[sw15073]
 gllm R package. gllm: Generalised loglinear model. Routines for loglinear models of incomplete...

kequate
 Referenced in 5 articles
[sw20025]
 search for a proper loglinear model in the presmoothing step...

confreq
 Referenced in 2 articles
[sw11694]
 antitype. CFA is similar to loglinear modeling. In loglinear modeling the goal ... significant residuals of a loglinear model. The book describes...

eMLEloglin
 Referenced in 2 articles
[sw17885]
 package eMLEloglin. Fitting logLinear Models in Sparse Contingency Tables. Loglinear modeling...

gRim
 Referenced in 3 articles
[sw20816]
 Models for for contingency tables (i.e. loglinear models) Graphical Gaussian models for multivariate normal...

PREG
 Referenced in 3 articles
[sw26380]
 linear regression model, (ii) a loglinear regression model, and (iii) a nonlinear regression model...

algstat
 Referenced in 3 articles
[sw20716]
 Current applications include exact inference in loglinear models for contingency table data, analysis...

AS 207
 Referenced in 2 articles
[sw27891]
 Algorithm AS 207: Fitting a General LogLinear Model...

multinom
 Referenced in 2 articles
[sw16499]
 Plus package multinom. Fits multinomial loglinear models via neural networks...

gvs_BUGS
 Referenced in 4 articles
[sw26317]
 within BUGS environment when the number of models is limited. We illustrate the application ... problems including linear regression, loglinear and binomial response models...

bayesloglin
 Referenced in 1 article
[sw19810]
 Data. The function MC3() searches for loglinear models with the highest posterior probability ... from the posterior distribution of the loglinear parameters. The functions findPostMean() and findPostCov() compute ... posterior mean and covariance matrix for decomposable models which, for these models, is available...