Package: EasyMx 0.4-2

EasyMx: Easy Model-Builder Functions for 'OpenMx'

Utilities for building certain kinds of common matrices and models in the extended structural equation modeling package, 'OpenMx'.

Authors:Michael D. Hunter [aut, cre], Joshua N. Pritikin [ctb]

EasyMx_0.4-2.tar.gz
EasyMx_0.4-2.zip(r-4.7)EasyMx_0.4-2.zip(r-4.6)EasyMx_0.4-2.zip(r-4.5)
EasyMx_0.4-2.tgz(r-4.6-any)EasyMx_0.4-2.tgz(r-4.5-any)
EasyMx_0.4-2.tar.gz(r-4.7-any)EasyMx_0.4-2.tar.gz(r-4.6-any)
EasyMx_0.4-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
EasyMx/json (API)

# Install 'EasyMx' in R:
install.packages('EasyMx', repos = c('https://mhunter1.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://bitbucket.org/mhunter/easymx

On CRAN:

Conda:

2.34 score 22 scripts 838 downloads 36 exports 15 dependencies

Last updated from:ada255285f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK146
source / vignettesOK176
linux-release-x86_64OK150
macos-release-arm64OK85
macos-oldrel-arm64OK104
windows-develOK115
windows-releaseOK104
windows-oldrelOK117
wasm-releaseOK109

Exports:emxARMAModelemxCholeskyComponentemxCholeskyVarianceemxCommonPathwayComponentemxCovariancesemxFactorModelemxGeneticFactorComponentemxGeneticFactorVarianceemxGrowthModelemxIndependentPathwayComponentemxKroneckerVarianceemxLoadingsemxLVARModelemxMeansemxMixtureModelemxModelARMAemxModelByIDemxModelFactoremxModelGrowthemxModelLVARemxModelMixtureemxModelRegressionemxModelStateSpaceMixtureemxModelTwinemxModelVARemxModelVARMAemxRegressionModelemxRelatednessMatrixemxResidualsemxStateSpaceMixtureClassifyemxStateSpaceMixtureModelemxThresholdsemxTwinModelemxVarianceComponentsemxVARMAModelemxVARModel

Dependencies:BHclidigestlatticelifecycleMASSMatrixmvtnormOpenMxRcppRcppEigenRcppParallelrlangrpfStanHeaders

Readme and manuals

Help Manual

Help pageTopics
EasyMx: Easy modeling in OpenMxEasyMx-package EasyMx
Creates component for a Biometric Cholesky ModelemxCholeskyComponent
Create a variance matrix in Cholesky formemxCholeskyVariance
Creates component for a Biometric Common Pathway ModelemxCommonPathwayComponent
Create a set of covariancesemxCovariances
Create a factor modelemxFactorModel emxModelFactor
Creates component for a Genetic Factor ModelemxGeneticFactorComponent
Creates a variance matrix accoring to the Genetic Factor ModelemxGeneticFactorVariance
Create a latent growth curve modelemxGrowthModel emxModelGrowth
Creates component for a Biometric Independent Pathway ModelemxIndependentPathwayComponent
Creates a large Variance matrix by Kroneckering two smaller matricesemxKroneckerVariance
Create a factor loadings matrixemxLoadings
Create a latent vector autoregressive (LVAR) modelemxLVARModel emxModelLVAR
Create a set of meansemxMeans
Create a mixture modelemxMixtureModel emxModelMixture
Create a model for each IDemxModelByID
Create a regression modelemxModelRegression emxRegressionModel
Create a relatedness matrixemxRelatednessMatrix
Create a residual variances matrixemxResiduals
Classify time series in a state space mixture modelemxStateSpaceMixtureClassify
Create a state space mixture modelemxModelStateSpaceMixture emxStateSpaceMixtureModel
Create a set of thresholds for ordinal dataemxThresholds
Creates behavior genetics Twin ModelemxModelTwin emxTwinModel
Creates Variance Components ModelemxVarianceComponents
Create a latent (vector) autoregressive moving average (ARMA) modelemxARMAModel emxModelARMA emxModelVARMA emxVARMAModel
Create a vector autoregressive (VAR) modelemxModelVAR emxVARModel