R: Optimal Subset Selection for Transformation Models

# Optimal Subset Selection for Transformation Models

## Documentation for package ‘tramvs’ version 0.0-7

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

abess_mmlt | Optimal subset selection for multivariate transformation models
abess_tram | Optimal subset selection for transformation models
AIC.tramvs | AIC "tramvs"
BoxCoxVS | Optimal subset selection in a BoxCox-type transformation model
coef.abess_tram | Coef "abess_tram"
coef.mmltvs | Coef "mmltvs"
coef.tramvs | Coef "tramvs"
ColrVS | Optimal subset selection in a Colr-type transformation model
cor_init | Compute correlation for initializing the active set
cor_init.default | Default method for computing correlation
cor_init.mmlt | Method for computing correlations in mmlts
cor_init.stram | Shit-scale tram method for computing correlation
cotramVS | Optimal subset selection in a cotram model
CoxphVS | Optimal subset selection in a Coxph-type transformation model
LehmannVS | Optimal subset selection in a Lehmann-type transformation model
LmVS | Optimal subset selection in an Lm-type transformation model
logLik.tramvs | logLik "tramvs"
mmltVS | Select optimal subset based on high dimensional BIC in mmlts
plot.tramvs | Plot "tramvs" object
PolrVS | Optimal subset selection in a Polr-type transformation model
predict.tramvs | Predict "tramvs"
print.tramvs | Print "tramvs"
residuals.tramvs | Residuals "tramvs"
SIC | SIC generic
SIC.tramvs | SIC "tramvs"
simulate.tramvs | Simulate "tramvs"
summary.tramvs | Summary "tramvs"
support.tramvs | Support "tramvs"
SurvregVS | Optimal subset selection in a Survreg model
tramvs | Select optimal subset based on high dimensional BIC