Package: lavaSearch2 2.0.3

Brice Ozenne

lavaSearch2: Tools for Model Specification in the Latent Variable Framework

Tools for model specification in the latent variable framework (add-on to the 'lava' package). The package contains three main functionalities: Wald tests/F-tests with improved control of the type 1 error in small samples, adjustment for multiple comparisons when searching for local dependencies, and adjustment for multiple comparisons when doing inference for multiple latent variable models.

Authors:Brice Ozenne [aut, cre]

lavaSearch2_2.0.3.tar.gz
lavaSearch2_2.0.3.tar.gz(r-4.5-noble)lavaSearch2_2.0.3.tar.gz(r-4.4-noble)
lavaSearch2_2.0.3.tgz(r-4.4-emscripten)lavaSearch2_2.0.3.tgz(r-4.3-emscripten)
lavaSearch2.pdf |lavaSearch2.html
lavaSearch2/json (API)
NEWS

# Install 'lavaSearch2' in R:
install.packages('lavaSearch2', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/bozenne/lavasearch2/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

3.86 score 140 scripts 2.6k downloads 63 exports 55 dependencies

Last updated 10 months agofrom:949a4e95c2. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linux-x86_64OKNov 20 2024

Exports:addLinkcalcDistMaxBootstrapcalcDistMaxIntegralcalcType1postSelectioncalibrateType1checkDatacleancoef2coefCovcoefExtracoefIndexModelcoefInterceptcoefRefcoefRegcoefTypecoefVarcombineFormulacompare2confint2createContrasteffects2estimate2extractDatafindNewLinkformula2charactergaussian_weight_gradient.lvmgaussian_weight_hessian.lvmgaussian_weight_logLik.lvmgaussian_weight_method.lvmgaussian_weight_objective.lvmgaussian_weight_score.lvmgaussian_weight.estimate.hookgetNewLinkgetNewModelgetStepgetVarCov2glht2hessian2iid2iid2plotiidJackinformation2initVarLinkinitVarLinksintDensTrileverage2matrixPowermodel.tables2modelsearch2moments2nobs2nStepresiduals2sampleRepeatedscore2sCorrectsCorrect<-setLinkskeletonsummary2transformSummaryTabletryWithWarningsvcov2

Dependencies:abindclicodetoolscolorspacedigestdoParallelfansifarverforeachfuturefuture.applyggplot2globalsgluegtableisobanditeratorslabelinglatticelavalifecyclelistenvmagrittrMASSMatrixmgcvmultcompmunsellmvtnormnlmenumDerivparallellypillarpkgconfigplyrprogressrR6RColorBrewerRcppRcppArmadilloreshape2rlangsandwichscalesSQUAREMstringistringrsurvivalTH.datatibbleutf8vctrsviridisLitewithrzoo

lavaSearch2: overview

Rendered fromoverview.pdf.asisusingR.rsp::asison Nov 20 2024.

Last update: 2024-01-24
Started: 2023-04-11

Readme and manuals

Help Manual

Help pageTopics
Add a New Link Between Two Variables in a LVMaddLink addLink.lvm addLink.lvm.reduced
Graphical Display of the Bias or Type 1 Errorautoplot.calibrateType1 autoplot_calibrateType1
2D-display of the Domain Used to Compute the Integralautoplot.intDensTri
Display the Value of a Coefficient across the Steps.autoplot.modelsearch2 autplot-modelsearch2
Adjust the p.values Using the Quantiles of the Max StatisticcalcDistMax calcDistMaxBootstrap calcDistMaxIntegral
Compute the Type 1 Error After Selection [EXPERIMENTAL]calcType1postSelection
Simulation Study Assessing Bias and Type 1 ErrorcalibrateType1 calibrateType1.lvm calibrateType1.lvmfit
Check that Validity of the DatasetcheckData checkData.lvm
Simplify a lvm objectclean clean.lvm
Model Coefficients With Small Sample Correctioncoef2 coef2.lvmfit
Extract the Coefficient by TypecoefByType coefCov coefCov.lvm coefCov.lvmfit coefCov.multigroup coefExtra coefExtra.lvm coefExtra.lvmfit coefExtra.multigroup coefIndexModel coefIndexModel.lvm coefIndexModel.lvmfit coefIndexModel.multigroup coefIndexModel.multigroupfit coefIntercept coefIntercept.lvm coefIntercept.lvmfit coefIntercept.multigroup coefRef coefRef.lvmfit coefReg coefReg.lvm coefReg.lvmfit coefReg.multigroup coefVar coefVar.lvm coefVar.lvmfit coefVar.multigroup
Extract the Type of Each CoefficientcoefType coefType.lvm coefType.lvmfit coefType.multigroup
Combine formulacombineFormula
Test Linear Hypotheses With Small Sample Correctioncompare.lvmfit2 compare2 compare2.lvmfit compare2.lvmfit2
Confidence Intervals With Small Sample Correctionconfint2 confint2.lvmfit model.tables2
formula character conversionconvFormulaCharacter formula2character
Create Contrast matrixcreateContrast createContrast.character createContrast.list createContrast.lvmfit createContrast.lvmfit2 createContrast.mmm
Degree of Freedom for the Chi-Square TestdfSigma
Effects Through Pathways With Small Sample Correctioneffects.lvmfit2 effects2 effects2.lvmfit effects2.lvmfit2
Extract Data From a Latent Variable ModelextractData extractData.lvmfit
Find all New Links Between VariablesfindNewLink findNewLink.lvm
Estimate LVM With Weightsgaussian_weight gaussian_weight.estimate.hook gaussian_weight_gradient.lvm gaussian_weight_hessian.lvm gaussian_weight_logLik.lvm gaussian_weight_method.lvm gaussian_weight_objective.lvm gaussian_weight_score.lvm
Extract the Links that Have Been Found by the modelsearch2.getNewLink getNewLink.modelsearch2
Extract the Model that Has Been Retains by the modelsearch2.getNewModel getNewModel.modelsearch2
Extract one Step From the Sequential ProceduregetStep getStep.modelsearch2
Residual Variance-Covariance Matrix With Small Sample Correction.getVarCov2 getVarCov2.lvmfit getVarCov2.lvmfit2
General Linear Hypothesis Testing With Small Sample Correctionglht.lvmfit2 glht2 glht2.lvmfit glht2.lvmfit2 glht2.mmm
Hessian With Small Sample Correction.hessian2 hessian2.lvmfit hessian2.lvmfit2
Influence Function With Small Sample Correction.iid.lvmfit2 iid2 iid2.lvmfit iid2.lvmfit2
Display the i.i.d. Decompositioniid2plot
Jackknife iid Decomposition from Model ObjectiidJack iidJack.default
Expected Information With Small Sample Correction.information.lvmfit2 information2 information2.lvmfit information2.lvmfit2
Normalize var1 and var2initVarLink initVarLinks
Integrate a Gaussian/Student Density over a TriangleintDensTri
Tools for Model Specification in the Latent Variable FrameworklavaSearch2-package lavaSearch2 lavaSearch2,
Leverage With Small Sample Correction.leverage2 leverage2.lvmfit leverage2.lvmfit2
Power of a MatrixmatrixPower
Data-driven Extension of a Latent Variable Modelmodelsearch2 modelsearch2.lvmfit
Effective Sample Size.nobs2 nobs2.lvmfit nobs2.lvmfit2
Find the Number of Steps Performed During the Sequential TestingnStep nStep.modelsearch2
Residuals With Small Sample Correction.residuals2 residuals2.lvmfit
Simulate Repeated Measurements over timesampleRepeated
Score With Small Sample Correctionscore.lvmfit2 score2 score2.lvmfit score2.lvmfit2
Depreciated Method For Small Sample CorrectionsCorrect sCorrect.default sCorrect<- sCorrect<-.default
Set a Link to a ValuesetLink setLink.lvm
Display the Type 1 Error Ratesummary.calibrateType1
Outcome of Linear Hypothesis Testingsummary.glht2
summary Method for modelsearch2 Objectssummary.modelsearch2
Latent Variable Model Summary After Small Sample Correctionsummary.lvmfit2 summary2 summary2.lvmfit summary2.lvmfit2
Apply Transformation to Summary TabletransformSummaryTable
Run an Expression and Catch Warnings and ErrorstryWithWarnings
Variance-Covariance With Small Sample Correctionvcov.lvmfit2 vcov2 vcov2.lvmfit vcov2.lvmfit2