int main(){
gsl_rng *r = apop_rng_alloc(10);
size_t i, ct = 5e4;
//set up the model & params
apop_data *d = apop_data_alloc(ct,2);
apop_data *params = apop_data_alloc(2,2,2);
apop_data_fill(params, 8, 1, 0.5,
2, 0.5, 1);
apop_model *pvm = apop_model_copy(apop_multivariate_normal);
pvm->parameters = apop_data_copy(params);
//make random draws from the multivar. normal
//this `pull a row view, fill its data element' form works for rows but not cols.
for(i=0; i< ct; i++){
Apop_row(d, i, onerow);
apop_draw(onerow->data, r, pvm);
}
//set up and estimate a model with fixed covariance matrix but free means
gsl_vector_set_all(pvm->parameters->vector, GSL_NAN);
apop_model *mep1 = apop_model_fix_params(pvm);
apop_model *e1 = apop_estimate(d, *mep1);
//compare results
printf("original params: ");
apop_vector_show(params->vector);
printf("estimated params: ");
apop_vector_show(e1->parameters->vector);
}
int main(){
apop_data *dataset = apop_text_to_data("data-regressme");
apop_model *est = apop_estimate(dataset, apop_ols);
printf("plot '-'\n");
strcpy(apop_opts.output_delimiter, "\n");
apop_vector_show(cooks_distance(est));
}
