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// Beta PDF
//
// beta_pdf - beta probability density
//
// f(x; α, β) = x^(α-1) * (1-x)^(β-1) / B(α, β), for 0 < x < 1
//
// Inputs: 1
// Outputs: 1 (PDF value)
// Constants: 2 (alpha, beta)
#include <math.h>
#include "ts.h"
typedef struct {
fp_t alpha;
fp_t beta;
} ts_beta_pdf_params_t;
ts_parameter_t const ts_beta_pdf_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 2, .params_size = sizeof(ts_beta_pdf_params_t) };
uint_t ts_beta_pdf_offset( ts_constant_t const *c )
{
( void )c;
return ( 0 );
}
int ts_beta_pdf(
fp_t * const *y, uint_t y_n,
fp_t const * const *x, uint_t x_n,
uint_t n, ts_constant_t const *c
)
{
TS_PROLOGUE( ts_beta_pdf_p );
if ( !c ) return -1;
fp_t alpha = ((ts_beta_pdf_params_t const *)c)->alpha;
fp_t beta = ((ts_beta_pdf_params_t const *)c)->beta;
if (isnan(alpha) || isnan(beta) || alpha <= 0 || beta <= 0)
{
for( uint_t i = 0; i < n; ++i ) y[0][i] = 0;
return -1;
}
fp_t beta_fn = exp( lgamma( alpha ) + lgamma( beta ) - lgamma( alpha + beta ) );
for( uint_t i = 0; i < n; ++i )
{
fp_t xi = x[0][i];
y[0][i] = ( xi > 0 && xi < 1 ) ? pow( xi, alpha - 1.0 ) * pow( 1.0 - xi, beta - 1.0 ) / beta_fn : 0.0;
}
return 0;
}
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