00001 #include <df1b2fun.h>
00002 #include <adrndeff.h>
00003 #include "statsLib.h"
00004
00005
00039 dvariable dbinom(const prevariable& x,const double& n,const double& p)
00040 {
00041 if(p<=0. && p>=1.0)
00042 {
00043 cerr<<"The probability p must be greater than 0 or less than 1 in "
00044 "dbinom(const prevariable& x,const double& n,const double& p)\n";
00045 return(0.0);
00046 }
00047
00048 RETURN_ARRAYS_INCREMENT();
00049 dvariable tmp = -log_comb(n,x)-x*log(p)-(n-x)*log(1.-p);
00050
00051 RETURN_ARRAYS_DECREMENT();
00052 return(tmp);
00053 }
00063 dvariable dbinom(const prevariable& x,const prevariable& n,const double& p)
00064 {
00065 if(p<=0. && p>=1.0)
00066 {
00067 cerr<<"The probability p must be greater than 0 or less than 1 in "
00068 "dbinom(const prevariable& x,const prevariable& n,const double& p)\n";
00069 return(0.0);
00070 }
00071
00072 RETURN_ARRAYS_INCREMENT();
00073 dvariable tmp = -log_comb(n,x)-x*log(p)-(n-x)*log(1.-p);
00074 RETURN_ARRAYS_DECREMENT();
00075 return(tmp);
00076 }
00086 dvariable dbinom(const prevariable& x,const prevariable& n,const prevariable& p)
00087 {
00088 if(p<=0. && p>=1.0)
00089 {
00090 cerr<<"The probability p must be greater than 0 or less than 1 in "
00091 "dbinom(const prevariable& x,const prevariable& n,const prevariable& p)\n";
00092 return(0.0);
00093 }
00094
00095 RETURN_ARRAYS_INCREMENT();
00096 dvariable tmp = -log_comb(n,x)-x*log(p)-(n-x)*log(1.-p);
00097 RETURN_ARRAYS_DECREMENT();
00098 return(tmp);
00099 }
00100
00110 dvariable dbinom(const dvar_vector& x,const dvar_vector& n,const dvar_vector& p)
00111 {
00112 if(min(p)<=0. && max(p)>=1.0)
00113 {
00114 cerr<<"The probability p must be greater than 0 or less than 1 in "
00115 "dbinom(const dvar_vector& x,const dvar_vector& n,const dvar_vector& p)\n";
00116 return(0.0);
00117 }
00118
00119 int i;
00120 int imin = x.indexmin();
00121 int imax = x.indexmax();
00122
00123 RETURN_ARRAYS_INCREMENT();
00124 dvariable tmp = 0.0;
00125 for(i=imin; i<=imax;i++)
00126 {
00127 tmp += log_comb(n(i),x(i))-x(i)*log(p(i))-(n(i)-x(i))*log(1.-p(i));
00128 }
00129
00130 RETURN_ARRAYS_DECREMENT();
00131 return(tmp);
00132 }
00133
00134 dvariable dbinom(const prevariable& x,const dvar_vector& n,const dvar_vector& p)
00135 {
00136 if(min(p)<=0. && max(p)>=1.0)
00137 {
00138 cerr<<"The probability p must be greater than 0 or less than 1 in "
00139 "dbinom(const prevariable& x,const dvar_vector& n,const dvar_vector& p)\n";
00140 return(0.0);
00141 }
00142
00143 int i;
00144 int imin = n.indexmin();
00145 int imax = n.indexmax();
00146
00147 RETURN_ARRAYS_INCREMENT();
00148 dvariable tmp = 0.0;
00149 for(i=imin; i<=imax;i++)
00150 {
00151 tmp += log_comb(n(i),x)-x*log(p(i))-(n(i)-x)*log(1.-p(i));
00152 }
00153
00154 RETURN_ARRAYS_DECREMENT();
00155 return(tmp);
00156 }
00157 dvariable dbinom(const dvar_vector& x,const prevariable& n,const dvar_vector& p)
00158 {
00159 if(min(p)<=0. && max(p)>=1.0)
00160 {
00161 cerr<<"The probability p must be greater than 0 or less than 1 in "
00162 "dbinom(const dvar_vector& x,const prevariable& n,const dvar_vector& p)\n";
00163 return(0.0);
00164 }
00165
00166 int i;
00167 int imin = x.indexmin();
00168 int imax = x.indexmax();
00169
00170 RETURN_ARRAYS_INCREMENT();
00171 dvariable tmp = 0.0;
00172 for(i=imin; i<=imax;i++)
00173 {
00174 tmp += log_comb(n,x(i))-x(i)*log(p(i))-(n-x(i))*log(1.-p(i));
00175 }
00176
00177 RETURN_ARRAYS_DECREMENT();
00178 return(tmp);
00179 }
00180 dvariable dbinom(const dvar_vector& x,const dvar_vector& n,const prevariable& p)
00181 {
00182 if(p<=0. && p>=1.0)
00183 {
00184 cerr<<"The probability p must be greater than 0 or less than 1 in "
00185 "dbinom(const dvar_vector& x,const dvar_vector& n,const prevariable& p)\n";
00186 return(0.0);
00187 }
00188
00189 int i;
00190 int imin = x.indexmin();
00191 int imax = x.indexmax();
00192
00193 RETURN_ARRAYS_INCREMENT();
00194 dvariable tmp = 0.0;
00195 for(i=imin; i<=imax;i++)
00196 {
00197 tmp += log_comb(n(i),x(i))-x(i)*log(p)-(n(i)-x(i))*log(1.-p);
00198 }
00199
00200 RETURN_ARRAYS_DECREMENT();
00201 return(tmp);
00202 }
00203 df1b2variable dbinom(const df1b2variable& x,const double& n,const double& p)
00204 {
00205 if(p<=0. && p>=1.0)
00206 {
00207 cerr<<"The probability p must be greater than 0 or less than 1 in "
00208 "dbinom(const df1b2variable& x,const double& n,const double& p)\n";
00209 return(0.0);
00210 }
00211
00212 RETURN_ARRAYS_INCREMENT();
00213 df1b2variable tmp = -log_comb(n,x)-x*log(p)-(n-x)*log(1.-p);
00214
00215 RETURN_ARRAYS_DECREMENT();
00216 return(tmp);
00217 }
00227 df1b2variable dbinom(const df1b2variable& x,const df1b2variable& n,const double& p)
00228 {
00229 if(p<=0. && p>=1.0)
00230 {
00231 cerr<<"The probability p must be greater than 0 or less than 1 in "
00232 "dbinom(const df1b2variable& x,const df1b2variable& n,const double& p)\n";
00233 return(0.0);
00234 }
00235
00236 RETURN_ARRAYS_INCREMENT();
00237 df1b2variable tmp = -log_comb(n,x)-x*log(p)-(n-x)*log(1.-p);
00238 RETURN_ARRAYS_DECREMENT();
00239 return(tmp);
00240 }
00250 df1b2variable dbinom(const df1b2variable& x,const df1b2variable& n,const df1b2variable& p)
00251 {
00252 if(value(p)<=0. && value(p)>=1.0)
00253 {
00254 cerr<<"The probability p must be greater than 0 or less than 1 in "
00255 "dbinom(const df1b2variable& x,const df1b2variable& n,const df1b2variable& p)\n";
00256 return(0.0);
00257 }
00258
00259 RETURN_ARRAYS_INCREMENT();
00260 df1b2variable tmp = -log_comb(n,x)-x*log(p)-(n-x)*log(1.-p);
00261 RETURN_ARRAYS_DECREMENT();
00262 return(tmp);
00263 }
00264
00274 df1b2variable dbinom(const df1b2vector& x,const df1b2vector& n,const df1b2vector& p)
00275 {
00276 if(min(value(p))<=0. && max(value(p))>=1.0)
00277 {
00278 cerr<<"The probability p must be greater than 0 or less than 1 in "
00279 "dbinom(const df1b2vector& x,const df1b2vector& n,const df1b2vector& p)\n";
00280 return(0.0);
00281 }
00282
00283 int i;
00284 int imin = x.indexmin();
00285 int imax = x.indexmax();
00286
00287 RETURN_ARRAYS_INCREMENT();
00288 df1b2variable tmp = 0.0;
00289 for(i=imin; i<=imax;i++)
00290 {
00291 tmp += log_comb(n(i),x(i))-x(i)*log(p(i))-(n(i)-x(i))*log(1.-p(i));
00292 }
00293
00294 RETURN_ARRAYS_DECREMENT();
00295 return(tmp);
00296 }
00297
00298 df1b2variable dbinom(const df1b2variable& x,const df1b2vector& n,const df1b2vector& p)
00299 {
00300 if(min(value(p))<=0. && max(value(p))>=1.0)
00301 {
00302 cerr<<"The probability p must be greater than 0 or less than 1 in "
00303 "dbinom(const df1b2variable& x,const df1b2vector& n,const df1b2vector& p)\n";
00304 return(0.0);
00305 }
00306
00307 int i;
00308 int imin = n.indexmin();
00309 int imax = n.indexmax();
00310
00311 RETURN_ARRAYS_INCREMENT();
00312 df1b2variable tmp = 0.0;
00313 for(i=imin; i<=imax;i++)
00314 {
00315 tmp += log_comb(n(i),x)-x*log(p(i))-(n(i)-x)*log(1.-p(i));
00316 }
00317
00318 RETURN_ARRAYS_DECREMENT();
00319 return(tmp);
00320 }
00321 df1b2variable dbinom(const df1b2vector& x,const df1b2variable& n,const df1b2vector& p)
00322 {
00323 if(min(value(p))<=0. && max(value(p))>=1.0)
00324 {
00325 cerr<<"The probability p must be greater than 0 or less than 1 in "
00326 "dbinom(const df1b2vector& x,const df1b2variable& n,const df1b2vector& p)\n";
00327 return(0.0);
00328 }
00329
00330 int i;
00331 int imin = x.indexmin();
00332 int imax = x.indexmax();
00333
00334 RETURN_ARRAYS_INCREMENT();
00335 df1b2variable tmp = 0.0;
00336 for(i=imin; i<=imax;i++)
00337 {
00338 tmp += log_comb(n,x(i))-x(i)*log(p(i))-(n-x(i))*log(1.-p(i));
00339 }
00340
00341 RETURN_ARRAYS_DECREMENT();
00342 return(tmp);
00343 }
00344 df1b2variable dbinom(const df1b2vector& x,const df1b2vector& n,const df1b2variable& p)
00345 {
00346 if(value(p)<=0. && value(p)>=1.0)
00347 {
00348 cerr<<"The probability p must be greater than 0 or less than 1 in "
00349 "dbinom(const df1b2vector& x,const df1b2vector& n,const df1b2variable& p)\n";
00350 return(0.0);
00351 }
00352
00353 int i;
00354 int imin = x.indexmin();
00355 int imax = x.indexmax();
00356
00357 RETURN_ARRAYS_INCREMENT();
00358 df1b2variable tmp = 0.0;
00359 for(i=imin; i<=imax;i++)
00360 {
00361 tmp += log_comb(n(i),x(i))-x(i)*log(p)-(n(i)-x(i))*log(1.-p);
00362 }
00363
00364 RETURN_ARRAYS_DECREMENT();
00365 return(tmp);
00366 }
1.8.0
