00001
00009 #include "party.h"
00010
00011
00021 void C_TeststatPvalue(const SEXP linexpcov, const SEXP varctrl,
00022 double *ans_teststat, double *ans_pvalue) {
00023
00024 double releps, abseps, tol;
00025 int maxpts;
00026
00027 maxpts = get_maxpts(varctrl);
00028 tol = get_tol(varctrl);
00029 abseps = get_abseps(varctrl);
00030 releps = get_releps(varctrl);
00031
00032
00033 ans_teststat[0] = C_TestStatistic(linexpcov, get_teststat(varctrl),
00034 get_tol(varctrl));
00035
00036
00037 if (get_pvalue(varctrl))
00038 ans_pvalue[0] = C_ConditionalPvalue(ans_teststat[0], linexpcov,
00039 get_teststat(varctrl),
00040 tol, &maxpts, &releps, &abseps);
00041 else
00042 ans_pvalue[0] = 1.0;
00043 }
00044
00053 void C_TeststatCriterion(const SEXP linexpcov, const SEXP varctrl,
00054 double *ans_teststat, double *ans_criterion) {
00055
00056 C_TeststatPvalue(linexpcov, varctrl, ans_teststat, ans_criterion);
00057
00058
00059
00060 if (get_pvalue(varctrl))
00061 ans_criterion[0] = 1 - ans_criterion[0];
00062 else
00063 ans_criterion[0] = ans_teststat[0];
00064
00065 }
00066
00067
00078 void C_IndependenceTest(const SEXP x, const SEXP y, const SEXP weights,
00079 SEXP linexpcov, SEXP varctrl,
00080 SEXP ans) {
00081
00082
00083
00084
00085 C_LinStatExpCov(REAL(x), ncol(x), REAL(y), ncol(y),
00086 REAL(weights), nrow(x), 1,
00087 GET_SLOT(linexpcov, PL2_expcovinfSym), linexpcov);
00088
00089
00090 if (get_teststat(varctrl) == 2)
00091 C_LinStatExpCovMPinv(linexpcov, get_tol(varctrl));
00092 C_TeststatPvalue(linexpcov, varctrl, &REAL(ans)[0], &REAL(ans)[1]);
00093 }
00094
00095
00105 SEXP R_IndependenceTest(SEXP x, SEXP y, SEXP weights, SEXP linexpcov, SEXP varctrl) {
00106
00107 SEXP ans;
00108
00109 PROTECT(ans = allocVector(REALSXP, 2));
00110 C_IndependenceTest(x, y, weights, linexpcov, varctrl, ans);
00111 UNPROTECT(1);
00112 return(ans);
00113 }
00114
00115
00130 void C_GlobalTest(const SEXP learnsample, const SEXP weights,
00131 SEXP fitmem, const SEXP varctrl,
00132 const SEXP gtctrl, const double minsplit,
00133 double *ans_teststat, double *ans_criterion, int depth) {
00134
00135 int ninputs, nobs, j, i, k, RECALC = 1, type;
00136 SEXP responses, inputs, y, x, xmem, expcovinf;
00137 SEXP Smtry;
00138 double *thisweights, *pvaltmp, stweights = 0.0;
00139 int RANDOM, mtry, *randomvar, *index;
00140 int *dontuse, *dontusetmp;
00141
00142 ninputs = get_ninputs(learnsample);
00143 nobs = get_nobs(learnsample);
00144 responses = GET_SLOT(learnsample, PL2_responsesSym);
00145 inputs = GET_SLOT(learnsample, PL2_inputsSym);
00146
00147
00148 y = get_test_trafo(responses);
00149
00150 expcovinf = GET_SLOT(fitmem, PL2_expcovinfSym);
00151 C_ExpectCovarInfluence(REAL(y), ncol(y), REAL(weights),
00152 nobs, expcovinf);
00153
00154 if (REAL(GET_SLOT(expcovinf, PL2_sumweightsSym))[0] < minsplit) {
00155 for (j = 0; j < ninputs; j++) {
00156 ans_teststat[j] = 0.0;
00157 ans_criterion[j] = 0.0;
00158 }
00159 } else {
00160
00161 dontuse = INTEGER(get_dontuse(fitmem));
00162 dontusetmp = INTEGER(get_dontusetmp(fitmem));
00163
00164 for (j = 0; j < ninputs; j++) dontusetmp[j] = !dontuse[j];
00165
00166
00167 RANDOM = get_randomsplits(gtctrl);
00168 Smtry = get_mtry(gtctrl);
00169 if (LENGTH(Smtry) == 1) {
00170 mtry = INTEGER(Smtry)[0];
00171 } else {
00172
00173 depth = (depth <= LENGTH(Smtry)) ? depth : LENGTH(Smtry);
00174 mtry = INTEGER(get_mtry(gtctrl))[depth - 1];
00175 }
00176 if (RANDOM & (mtry > ninputs)) {
00177 warning("mtry is larger than ninputs, using mtry = inputs");
00178 mtry = ninputs;
00179 RANDOM = 0;
00180 }
00181 if (RANDOM) {
00182 index = Calloc(ninputs, int);
00183 randomvar = Calloc(mtry, int);
00184 C_SampleNoReplace(index, ninputs, mtry, randomvar);
00185 j = 0;
00186 for (k = 0; k < mtry; k++) {
00187 j = randomvar[k];
00188 while(dontuse[j] && j < ninputs) j++;
00189 if (j == ninputs)
00190 error("not enough variables to sample from");
00191 dontusetmp[j] = 0;
00192 }
00193 Free(index);
00194 Free(randomvar);
00195 }
00196
00197 for (j = 1; j <= ninputs; j++) {
00198
00199 if ((RANDOM && dontusetmp[j - 1]) || dontuse[j - 1]) {
00200 ans_teststat[j - 1] = 0.0;
00201 ans_criterion[j - 1] = 0.0;
00202 continue;
00203 }
00204
00205 x = get_transformation(inputs, j);
00206
00207 xmem = get_varmemory(fitmem, j);
00208 if (!has_missings(inputs, j)) {
00209 C_LinStatExpCov(REAL(x), ncol(x), REAL(y), ncol(y),
00210 REAL(weights), nrow(x), !RECALC, expcovinf,
00211 xmem);
00212 } else {
00213 thisweights = C_tempweights(j, weights, fitmem, inputs);
00214
00215
00216
00217
00218
00219
00220 stweights = 0.0;
00221 for (i = 0; i < nobs; i++) stweights += thisweights[i];
00222 if (stweights < minsplit) {
00223 ans_teststat[j - 1] = 0.0;
00224 ans_criterion[j - 1] = 0.0;
00225 continue;
00226 }
00227
00228 C_LinStatExpCov(REAL(x), ncol(x), REAL(y), ncol(y),
00229 thisweights, nrow(x), RECALC,
00230 GET_SLOT(xmem, PL2_expcovinfSym),
00231 xmem);
00232 }
00233
00234 if (get_teststat(varctrl) == 2)
00235 C_LinStatExpCovMPinv(xmem, get_tol(varctrl));
00236 C_TeststatCriterion(xmem, varctrl, &ans_teststat[j - 1],
00237 &ans_criterion[j - 1]);
00238 }
00239
00240 type = get_testtype(gtctrl);
00241 switch(type) {
00242
00243 case BONFERRONI:
00244 for (j = 0; j < ninputs; j++)
00245 ans_criterion[j] = R_pow_di(ans_criterion[j], ninputs);
00246 break;
00247
00248 case MONTECARLO:
00249 pvaltmp = Calloc(ninputs, double);
00250 C_MonteCarlo(ans_criterion, learnsample, weights, fitmem,
00251 varctrl, gtctrl, pvaltmp);
00252 for (j = 0; j < ninputs; j++)
00253 ans_criterion[j] = 1 - pvaltmp[j];
00254 Free(pvaltmp);
00255 break;
00256
00257 case AGGREGATED:
00258 error("C_GlobalTest: aggregated global test not yet implemented");
00259 break;
00260
00261 case UNIVARIATE: break;
00262 case TESTSTATISTIC: break;
00263 default: error("C_GlobalTest: undefined value for type argument");
00264 break;
00265 }
00266 }
00267 }
00268
00269
00279 SEXP R_GlobalTest(SEXP learnsample, SEXP weights, SEXP fitmem,
00280 SEXP varctrl, SEXP gtctrl) {
00281
00282 SEXP ans, teststat, criterion;
00283
00284 GetRNGstate();
00285
00286 PROTECT(ans = allocVector(VECSXP, 2));
00287 SET_VECTOR_ELT(ans, 0,
00288 teststat = allocVector(REALSXP, get_ninputs(learnsample)));
00289 SET_VECTOR_ELT(ans, 1,
00290 criterion = allocVector(REALSXP, get_ninputs(learnsample)));
00291
00292 C_GlobalTest(learnsample, weights, fitmem, varctrl, gtctrl, 0,
00293 REAL(teststat), REAL(criterion), 1);
00294
00295 PutRNGstate();
00296
00297 UNPROTECT(1);
00298 return(ans);
00299 }