#include "party.h"

Go to the source code of this file.
Functions | |
| double | C_quadformConditionalPvalue (const double tstat, const double df) |
| SEXP | R_quadformConditionalPvalue (SEXP tstat, SEXP df) |
| double | C_maxabsConditionalPvalue (const double tstat, const double *Sigma, const int pq, int *maxpts, double *releps, double *abseps, double *tol) |
| SEXP | R_maxabsConditionalPvalue (SEXP tstat, SEXP Sigma, SEXP maxpts, SEXP releps, SEXP abseps, SEXP tol) |
| void | C_MonteCarlo (double *criterion, SEXP learnsample, SEXP weights, SEXP fitmem, SEXP varctrl, SEXP gtctrl, double *ans_pvalues) |
| SEXP | R_MonteCarlo (SEXP criterion, SEXP learnsample, SEXP weights, SEXP fitmem, SEXP varctrl, SEXP gtctrl) |
Definition in file Distributions.c.
| double C_maxabsConditionalPvalue | ( | const double | tstat, | |
| const double * | Sigma, | |||
| const int | pq, | |||
| int * | maxpts, | |||
| double * | releps, | |||
| double * | abseps, | |||
| double * | tol | |||
| ) |
Conditional asymptotic P-value of a maxabs-type test statistic
Basically the functionality from package `mvtnorm'
| tstat | test statitstic | |
| Sigma | covariance matrix | |
| pq | nrow(Sigma) | |
| maxpts | number of Monte-Carlo steps | |
| releps | relative error | |
| abseps | absolute error | |
| tol | tolerance |
Definition at line 52 of file Distributions.c.
Referenced by C_ConditionalPvalue(), and R_maxabsConditionalPvalue().
| void C_MonteCarlo | ( | double * | criterion, | |
| SEXP | learnsample, | |||
| SEXP | weights, | |||
| SEXP | fitmem, | |||
| SEXP | varctrl, | |||
| SEXP | gtctrl, | |||
| double * | ans_pvalues | |||
| ) |
Monte-Carlo approximation to the conditional pvalues
| criterion | vector of node criteria for each input | |
| learnsample | an object of class `LearningSample' | |
| weights | case weights | |
| fitmem | an object of class `TreeFitMemory' | |
| varctrl | an object of class `VariableControl' | |
| gtctrl | an object of class `GlobalTestControl' | |
| ans_pvalues | return values; vector of adjusted pvalues |
Definition at line 169 of file Distributions.c.
Referenced by C_GlobalTest(), and R_MonteCarlo().
| double C_quadformConditionalPvalue | ( | const double | tstat, | |
| const double | df | |||
| ) |
Conditional asymptotic P-value of a quadratic form
| tstat | test statistic | |
| df | degree of freedom |
Definition at line 18 of file Distributions.c.
Referenced by C_ConditionalPvalue(), and R_quadformConditionalPvalue().
| SEXP R_maxabsConditionalPvalue | ( | SEXP | tstat, | |
| SEXP | Sigma, | |||
| SEXP | maxpts, | |||
| SEXP | releps, | |||
| SEXP | abseps, | |||
| SEXP | tol | |||
| ) |
R-interface to C_maxabsConditionalPvalue
| tstat | test statitstic | |
| Sigma | covariance matrix | |
| maxpts | number of Monte-Carlo steps | |
| releps | relative error | |
| abseps | absolute error | |
| tol | tolerance |
Definition at line 142 of file Distributions.c.
References C_maxabsConditionalPvalue(), and nrow().

| SEXP R_MonteCarlo | ( | SEXP | criterion, | |
| SEXP | learnsample, | |||
| SEXP | weights, | |||
| SEXP | fitmem, | |||
| SEXP | varctrl, | |||
| SEXP | gtctrl | |||
| ) |
R-interface to C_MonteCarlo
| criterion | vector of node criteria for each input | |
| learnsample | an object of class `LearningSample' | |
| weights | case weights | |
| fitmem | an object of class `TreeFitMemory' | |
| varctrl | an object of class `VariableControl' | |
| gtctrl | an object of class `GlobalTestControl' |
Definition at line 278 of file Distributions.c.
References C_MonteCarlo(), and get_ninputs().

| SEXP R_quadformConditionalPvalue | ( | SEXP | tstat, | |
| SEXP | df | |||
| ) |
R-interface to C_quadformConditionalPvalue
| tstat | test statitstic | |
| df | degree of freedom |
Definition at line 29 of file Distributions.c.
References C_quadformConditionalPvalue().

1.5.3