Package: mme 0.1-6

mme: Multinomial Mixed Effects Models

Fit Gaussian Multinomial mixed-effects models for small area estimation: Model 1, with one random effect in each category of the response variable (Lopez-Vizcaino,E. et al., 2013) <doi:10.1177/1471082X13478873>; Model 2, introducing independent time effect; Model 3, introducing correlated time effect. mme calculates direct and parametric bootstrap MSE estimators (Lopez-Vizcaino,E et al., 2014) <doi:10.1111/rssa.12085>.

Authors:E. Lopez-Vizcaino, M.J. Lombardia and D. Morales

mme_0.1-6.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mme/json (API)

# Install 'mme' in R:

install.packages('mme', repos = c('https://mestherlv.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

simdata - Dataset for Model 1
simdata2 - Dataset for Model 2
simdata3 - Dataset for Model 3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.66 score 1 stars 46 scripts 259 downloads 30 exports 3 dependencies

Last updated from:3acfdec03f. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	185
source / vignettes	OK	147
linux-release	OK	137
macos-release	OK	196
macos-oldrel	OK	149
windows-devel	OK	81
windows-release	OK	91
windows-oldrel	OK	79
wasm-release	OK	72

Exports:addtolist addtomatrix ci data.mme Fbetaf Fbetaf.ct Fbetaf.it initial.values mmedata model modelfit1 modelfit2 modelfit3 mseb msef msef.ct msef.it omega phi.direct phi.direct.ct phi.direct.it phi.mult phi.mult.ct phi.mult.it prmu prmu.time sPhikf sPhikf.ct sPhikf.it wmatrix

Dependencies:lattice MASS Matrix

mme: tutorial for mme package

Overview | Models | The package mme | Example to fit model 1

Rendered frommme_vignette.Rnwusingutils::Sweave

Last update: 2013-06-10
Started: 2013-06-10

Help page	Topics
Multinomial Mixed Effects Models	mme-package mme
Add items from a list	addtolist
Add rows from a matrix	addtomatrix
Standard deviation and p-values of the estimated model parameters	ci
Function to generate matrices and the initial values	data.mme
Inverse of the Fisher information matrix of the fixed and random effects in Model 1	Fbetaf
Inverse of the Fisher information matrix of fixed and random effects in Model 3	Fbetaf.ct
The inverse of the Fisher information matrix of the fixed and random effects for Model 2	Fbetaf.it
Initial values for fitting algorithm to estimate the fixed and random effects and the variance components	initial.values
Create objects of class mmedata	mmedata
Choose between the three models	model
Function used to fit Model 1	modelfit1
Function to fit Model 2	modelfit2
Function used to fit Model 3	modelfit3
Bias and MSE using parametric bootstrap	mseb
Analytic MSE for Model 1	msef
Analytic MSE for Model 3	msef.ct
Analytic MSE for Model 2	msef.it
Model correlation matrix for Model 3	omega
Variance components for Model 1	phi.direct
Variance components for Model 3	phi.direct.ct
Variance components for Model 2	phi.direct.it
Initial values for the variance components for Model 1	phi.mult
Initial values for the variance components in Model 3	phi.mult.ct
Initial values for the variance components in Model 2	phi.mult.it
Print objects of class mme	print.mme
Estimated mean and probabilities for Model 1	prmu
Estimated mean and probabilities for Model 2 and 3	prmu.time
Dataset for Model 1	simdata
Dataset for Model 2	simdata2
Dataset for Model 3	simdata3
Fisher information matrix and score vectors of the variance components for Model 1	sPhikf
Fisher information matrix and score vectors of the variance components for Model 3	sPhikf.ct
Fisher information matrix and score vectors of the variance components for Model 2	sPhikf.it
Model variance-covariance matrix of the multinomial mixed models	wmatrix

Package: mme 0.1-6

mme: Multinomial Mixed Effects Models

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Help Manual

Usage by other packages (reverse dependencies)