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// Time Series Forecast
//
// time_series_forecast
//
// Time Series Forecast
//
//
//
// Inputs: 1
// Outputs: 1
// Constants: 0
#include <math.h>
#include "ts.h"
ts_parameter_t const ts_time_series_forecast_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 0, .params_size = 0 };
uint_t ts_time_series_forecast_offset( ts_constant_t const *c )
{
( void )c;
return ( 4 );
}
int ts_time_series_forecast(
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_time_series_forecast_p );
(void)c;
for ( uint_t j = 0; j < n && j < 4; ++j ) y[0][j] = 0;
for ( uint_t i = 4; i < n; ++i )
{
fp_t sum_x = 0, sum_y = 0, sum_xy = 0, sum_x2 = 0;
for ( uint_t j = 0; j < 5; ++j )
{
fp_t xv = (fp_t)j;
fp_t yv = x[0][i - 4 + j];
sum_x += xv;
sum_y += yv;
sum_xy += xv * yv;
sum_x2 += xv * xv;
}
fp_t denom = 5.0 * sum_x2 - sum_x * sum_x;
if (denom == 0) {
y[0][i] = sum_y / 5.0;
} else {
fp_t slope = (5.0 * sum_xy - sum_x * sum_y) / denom;
fp_t intercept = (sum_y - slope * sum_x) / 5.0;
y[0][i] = intercept + slope * 5.0;
}
}
return 0;
}
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