 	printf("Finished.  nsamps=%d\n", nsamps_tot);
 	printf("Computing Sample mean...\n");
 	compute_sample_mean<<<N, 1>>>(samples, sample_mean, nsamps_tot, N);
-
-	/*copy back sample mean*/
+	compute_sample_covariance<<<N, N>>>(samples, sample_covariance, nsamps_tot, N);
+	/*copy back sample  mean*/
 	cudaMemcpy(sample_mean_res, sample_mean, mean_size, cudaMemcpyDeviceToHost);
 	cudaMemcpy(samples_res, samples, samples_size, cudaMemcpyDeviceToHost);
+	cudaMemcpy(sample_covariance_res, sample_covariance, cov_size, cudaMemcpyDeviceToHost);
 
 	/* Display*/
 	for(i=0; i<N; i++)

	float *alpha_res = (float*)malloc(mean_size);
	float *beta_res = (float*)malloc(cov_size);
	float *sample_mean_res = (float*)malloc(mean_size);
	float *samples_res = (float*)malloc(samples_size);

	/* Allocate device memory */

	sample_mean[cell] = sample_mean[cell] / nsamps;
}

__global__ void compute_sample_covariance(float* samples, float* sample_covariance, int nsamps, int N)
{
	int i = blockIdx.x;
	int j = threadIdx.x;
	sample_covariance[i*N + j] = 0.0;
	for(int samp = 0; samp<nsamps; samp++)
	{
		sample_covariance[i*N+j] += samples[samp*N+i]*samples[samp*N+j];
	}
	sample_covariance[i*N+j] = sample_covariance[i*N+j]/nsamps;

}


__global__ void update_parameter_estimates(float* alpha, float* beta, float* sample_mean, float* sample_covariance, int N)
{
