AIC.tramvs              AIC "tramvs"
BoxCoxVS                Optimal subset selection in a BoxCox-type
                        transformation model
ColrVS                  Optimal subset selection in a Colr-type
                        transformation 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
PolrVS                  Optimal subset selection in a Polr-type
                        transformation model
SIC                     SIC generic
SIC.tramvs              SIC "tramvs"
SurvregVS               Optimal subset selection in a Survreg model
abess_mmlt              Optimal subset selection for multivariate
                        transformation models
abess_tram              Optimal subset selection for transformation
                        models
coef.abess_tram         Coef "abess_tram"
coef.mmltvs             Coef "mmltvs"
coef.tramvs             Coef "tramvs"
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
logLik.tramvs           logLik "tramvs"
mmltVS                  Select optimal subset based on high dimensional
                        BIC in mmlts
plot.tramvs             Plot "tramvs" object
predict.tramvs          Predict "tramvs"
print.tramvs            Print "tramvs"
residuals.tramvs        Residuals "tramvs"
simulate.tramvs         Simulate "tramvs"
summary.tramvs          Summary "tramvs"
support.tramvs          Support "tramvs"
tramvs                  Select optimal subset based on high dimensional
                        BIC
