CFA_data | CFA example data |
compute_sc | Compute the GLM systematic component. |
cp_AIC | Compute Akaike's information criterion |
cp_BIC | Compute bayesian information criterion |
cp_F | Compute F statistic |
cp_gR2 | Compute generalized R-squared |
cp_LRT | Compute likelihood ratio test |
cp_thrs_LLS | Compute threshold values based on Log-likelihood values |
cp_thrs_NOR | Compute normalized association measure |
cp_thrs_PR2 | Compute threshold values based on the pseudo R2 |
cp_validation_fit | Compute fit measure(s) on the validation data set |
cv_average | Average fit measures computed in the K-fold cross-validation... |
cv_choose | Cross-validation choice |
cv_gspcr | Cross-validation of Generalized Principal Component... |
est_gspcr | Estimate Generalized Principal Component Regression |
est_univ_mods | Estimate simple GLM models |
GSPCRexdata | GSPCR example data |
gspcr-package | gspcr: Generalized Supervised Principal Component Regression |
LL_baseline | Baseline category logistic regression log-likelihood |
LL_binomial | Binomial log-likelihood |
LL_cumulative | Proportional odds model log-likelihood |
LL_gaussian | Gaussian log-likelihood |
LL_newdata | Log-Likelihood for new data |
LL_poisson | Poisson regression log-likelihood |
pca_mix | PCA of a mixture of numerical and categorical data |
plot.gspcrcv | Plot the cross-validation solution path for the GSPCR... |
predict.gspcrout | Predict GSPCR model dependent variable scores |
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