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#include <R.h>
#include "mcmc.h"
/* overlapping batch means for vector time series
*
* input:
*
* x time series, n x p matrix, n time points and p components
* len batch length
*
* output:
*
* mean sample mean, a p vector
* var estimated variance of sample mean, a p x p matrix
*
*/
#define X(I,J) x[(I) + n * (J)]
#define VAR(I,J) var[(I) + p * (J)]
void olbm(double *x, int *nin, int *pin, int *lin, double *mean,
double *var, int *nocalcin)
{
int n = nin[0];
int p = pin[0];
int len = lin[0];
double nbatch = n - len + 1;
int nocalc = nocalcin[0];
double *work = (double *) R_alloc(p, sizeof(double));
int i, j, k, l;
if (len > n)
error("len > n\n");
if (! nocalc)
for (i=0; i<p; i++) {
double sum = 0.0;
for (k=0; k<n; k++)
sum += X(k,i);
mean[i] = sum / n;
}
/* easier to work with len * means, change means to that until
* further notice
*/
for (i=0; i<p; i++)
mean[i] *= len;
for (i=0; i<p; i++) {
work[i] = 0.0;
for (k=0; k<len; k++)
work[i] += X(k,i);
for (j=i; j>=0; j--)
VAR(i,j) = (work[i] - mean[i]) * (work[j] - mean[j]);
}
for (k=0, l=len; l<n; k++, l++)
for (i=0; i<p; i++) {
work[i] -= X(k,i);
work[i] += X(l,i);
for (j=i; j>=0; j--)
VAR(i,j) += (work[i] - mean[i]) *
(work[j] - mean[j]);
}
/* fix up means and variances, divide out factors of len and len^2 */
for (i=0; i<p; i++)
mean[i] /= len;
for (i=0; i<p; i++)
for (j=0; j<=i; j++) {
VAR(i,j) /= nbatch * n * len;
if (j < i) VAR(j,i) = VAR(i,j);
}
}
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