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); } }