static double f_zinb_reg(const gsl_vector *v, void *params){
int i, binnum;
double p, n, m, p0, r, fxy=0;
ParStr *par = (ParStr *)params;
p = gsl_vector_get(v, 0);
n = gsl_vector_get(v, 1);
m = gsl_vector_get(v, 2);
printf("zinb_reg p=%f, n=%f, m=%f\n",p, n, m);
binnum = par->binnum;
TYPE_WIGARRAY *wig = par->wig;
TYPE_WIGARRAY *mp = par->mp;
for(i=0; i<binnum; i++){ /* wig[i]が得られる確率を最大化 */
if(!mp[i]) p0=1; else p0 = gsl_sf_beta(WIGARRAY2VALUE(mp[i]), m);
printf("%d p0=%f\n", i, p0);
if(!wig[i]){
r = p0 + (1 - p0) * gsl_ran_negative_binomial_pdf(0, p, n);
}else{
r = (1 - p0) * gsl_ran_negative_binomial_pdf(WIGARRAY2VALUE(wig[i]), p, n);
}
fxy += log(r);
}
printf("fxy=%f\n",fxy);
return fxy;
}
double pw_get_zeroinflated_negative_binomial(int k, double p, double n, double p0){
double r;
if(!k){
r = p0 + (1 - p0) * gsl_ran_negative_binomial_pdf(0, p, n);
}else{
r = (1 - p0) * gsl_ran_negative_binomial_pdf(k, p, n);
}
return r;
}
static double f_zinb_const(const gsl_vector *v, void *params){
int i;
double p, n, r=0, fxy=0, p0;
double *par = (double *)params;
p = gsl_vector_get(v, 0);
if(p<=0) p=0.01;
if(p>=1) p=0.99;
n = gsl_vector_get(v, 1);
p0 = gsl_vector_get(v, 2);
if(p0<0) p0=0;
if(p0>1) p0=1.0;
LOG("zinb_const p=%f, n=%f, p0=%f\n", p, n, p0);
for(i=0; i<thre; i++){
double rtemp = r;
if(!i) r = p0 + (1 - p0) * gsl_ran_negative_binomial_pdf(0, p, n);
else r = (1 - p0) * gsl_ran_negative_binomial_pdf(i, p, n);
if(isinf(r) || isnan(r)) r = rtemp;
// printf("%d: %f - %f\n", i, par[i] , r);
fxy += (par[i] - r)*(par[i] - r);
}
return fxy;
}
double
test_negative_binomial_pdf (unsigned int n)
{
return gsl_ran_negative_binomial_pdf (n, 0.3, 20.0);
}
double
gsl_ran_pascal_pdf (const unsigned int k, const double p, unsigned int n)
{
double P = gsl_ran_negative_binomial_pdf (k, p, (double) n);
return P;
}
double pw_get_negative_binomial(int k, double p, double n){
return gsl_ran_negative_binomial_pdf(k, p, n);
}
int main(int argc, char **argv){
distlist distribution = Normal;
char msg[10000], c;
int pval = 0, qval = 0;
double param1 = GSL_NAN, param2 =GSL_NAN, findme = GSL_NAN;
char number[1000];
sprintf(msg, "%s [opts] number_to_lookup\n\n"
"Look up a probability or p-value for a given standard distribution.\n"
"[This is still loosely written and counts as beta. Notably, negative numbers are hard to parse.]\n"
"E.g.:\n"
"%s -dbin 100 .5 34\n"
"sets the distribution to a Binomial(100, .5), and find the odds of 34 appearing.\n"
"%s -p 2 \n"
"find the area of the Normal(0,1) between -infty and 2. \n"
"\n"
"-pval Find the p-value: integral from -infinity to your value\n"
"-qval Find the q-value: integral from your value to infinity\n"
"\n"
"After giving an optional -p or -q, specify the distribution. \n"
"Default is Normal(0, 1). Other options:\n"
"\t\t-binom Binomial(n, p)\n"
"\t\t-beta Beta(a, b)\n"
"\t\t-f F distribution(df1, df2)\n"
"\t\t-norm Normal(mu, sigma)\n"
"\t\t-negative bin Negative binomial(n, p)\n"
"\t\t-poisson Poisson(L)\n"
"\t\t-t t distribution(df)\n"
"I just need enough letters to distinctly identify a distribution.\n"
, argv[0], argv[0], argv[0]);
opterr=0;
if(argc==1){
printf("%s", msg);
return 0;
}
while ((c = getopt (argc, argv, "B:b:F:f:N:n:pqT:t:")) != -1){
switch (c){
case 'B':
case 'b':
if (optarg[0]=='i')
distribution = Binomial;
else if (optarg[0]=='e')
distribution = Beta;
else {
printf("I can't parse the option -b%s\n", optarg);
exit(0);
}
param1 = atof(argv[optind]);
param2 = atof(argv[optind+1]);
findme = atof(argv[optind+2]);
break;
case 'F':
case 'f':
distribution = F;
param1 = atof(argv[optind]);
findme = atof(argv[optind+1]);
break;
case 'H':
case 'h':
printf("%s", msg);
return 0;
case 'n':
case 'N':
if (optarg[0]=='o'){ //normal
param1 = atof(argv[optind]);
param2 = atof(argv[optind+1]);
findme = atof(argv[optind+2]);
} else if (optarg[0]=='e'){
distribution = Negbinom;
param1 = atof(argv[optind]);
param2 = atof(argv[optind+1]);
findme = atof(argv[optind+2]);
} else {
printf("I can't parse the option -n%s\n", optarg);
exit(0);
}
break;
case 'p':
if (!optarg || optarg[0] == 'v')
pval++;
else if (optarg[0] == 'o'){
distribution = Poisson;
param1 = atof(argv[optind]);
findme = atof(argv[optind+1]);
} else {
printf("I can't parse the option -p%s\n", optarg);
exit(0);
}
break;
case 'q':
qval++;
break;
case 'T':
case 't':
distribution = T;
param1 = atof(argv[optind]);
findme = atof(argv[optind+1]);
break;
case '?'://probably a negative number
if (optarg)
snprintf(number, 1000, "%c%s", optopt, optarg);
else snprintf(number, 1000, "%c", optopt);
if (gsl_isnan(param1)) param1 = -atof(number);
else if (gsl_isnan(param2)) param2 = -atof(number);
else if (gsl_isnan(findme)) findme = -atof(number);
}
}
if (gsl_isnan(findme)) findme = atof(argv[optind]);
//defaults, as promised
if (gsl_isnan(param1)) param1 = 0;
if (gsl_isnan(param2)) param2 = 1;
if (!pval && !qval){
double val =
distribution == Beta ? gsl_ran_beta_pdf(findme, param1, param2)
: distribution == Binomial ? gsl_ran_binomial_pdf(findme, param2, param1)
: distribution == F ? gsl_ran_fdist_pdf(findme, param1, param2)
: distribution == Negbinom ? gsl_ran_negative_binomial_pdf(findme, param2, param1)
: distribution == Normal ? gsl_ran_gaussian_pdf(findme, param2)+param1
: distribution == Poisson ? gsl_ran_poisson_pdf(findme, param1)
: distribution == T ? gsl_ran_tdist_pdf(findme, param1) : GSL_NAN;
printf("%g\n", val);
return 0;
}
if (distribution == Binomial){
printf("Sorry, the GSL doesn't have a Binomial CDF.\n");
return 0; }
if (distribution == Negbinom){
printf("Sorry, the GSL doesn't have a Negative Binomial CDF.\n");
return 0; }
if (distribution == Poisson){
printf("Sorry, the GSL doesn't have a Poisson CDF.\n");
return 0; }
if (pval){
double val =
distribution == Beta ? gsl_cdf_beta_P(findme, param1, param2)
: distribution == F ? gsl_cdf_fdist_P(findme, param1, param2)
: distribution == Normal ? gsl_cdf_gaussian_P(findme-param1, param2)
: distribution == T ? gsl_cdf_tdist_P(findme, param1) : GSL_NAN;
printf("%g\n", val);
return 0;
}
if (qval){
double val =
distribution == Beta ? gsl_cdf_beta_Q(findme, param1, param2)
: distribution == F ? gsl_cdf_fdist_Q(findme, param1, param2)
: distribution == Normal ? gsl_cdf_gaussian_Q(findme-param1, param2)
: distribution == T ? gsl_cdf_tdist_Q(findme, param1) : GSL_NAN;
printf("%g\n", val);
}
}
