Man pages for gspcr
Generalized Supervised Principal Component Regression

CFA_dataCFA example data
compute_scCompute the GLM systematic component.
cp_AICCompute Akaike's information criterion
cp_BICCompute bayesian information criterion
cp_FCompute F statistic
cp_gR2Compute generalized R-squared
cp_LRTCompute likelihood ratio test
cp_thrs_LLSCompute threshold values based on Log-likelihood values
cp_thrs_NORCompute normalized association measure
cp_thrs_PR2Compute threshold values based on the pseudo R2
cp_validation_fitCompute fit measure(s) on the validation data set
cv_averageAverage fit measures computed in the K-fold cross-validation...
cv_chooseCross-validation choice
cv_gspcrCross-validation of Generalized Principal Component...
est_gspcrEstimate Generalized Principal Component Regression
est_univ_modsEstimate simple GLM models
GSPCRexdataGSPCR example data
gspcr-packagegspcr: Generalized Supervised Principal Component Regression
LL_baselineBaseline category logistic regression log-likelihood
LL_binomialBinomial log-likelihood
LL_cumulativeProportional odds model log-likelihood
LL_gaussianGaussian log-likelihood
LL_newdataLog-Likelihood for new data
LL_poissonPoisson regression log-likelihood
pca_mixPCA of a mixture of numerical and categorical data
plot.gspcrcvPlot the cross-validation solution path for the GSPCR...
predict.gspcroutPredict GSPCR model dependent variable scores
gspcr documentation built on May 29, 2024, 2:44 a.m.