C++ (Cpp) gretl_model_allocate_param_namesの例

コード例 #1

ファイル: gretl_midas.c プロジェクト: HelioGuilherme66/gretl

static int finalize_midas_model (MODEL *pmod,
				 const int *list,
				 const char *param,
				 const DATASET *dset,
				 midas_info *minfo,
				 int nmidas,
				 int *xlist,
				 int ldepvar,
				 int hfslopes)
{
    int type0, mixed = 0;
    int i, err = 0;

    gretl_model_set_string_as_data(pmod, "midas_spec",
				   gretl_strdup(param));

    if (pmod->ci == OLS) {
	/* @pmod is the result of OLS estimation */
	int vi;
	
	gretl_model_allocate_param_names(pmod, pmod->ncoeff);
	for (i=0; i<pmod->ncoeff; i++) {
	    vi = pmod->list[i+2];
	    gretl_model_set_param_name(pmod, i, dset->varname[vi]);
	}
	gretl_model_set_int(pmod, "umidas", 1);
    } else {
	/* @pmod is the result of NLS estimation */
	free(pmod->depvar);
	pmod->depvar = gretl_strdup(dset->varname[list[1]]);
	free(pmod->list);
	pmod->list = gretl_list_copy(list);
    }

    pmod->ci = MIDASREG;

    /* record list of low-frequency regressors */
    gretl_model_set_list_as_data(pmod, "lfxlist", xlist);

    if (ldepvar) {
	gretl_model_set_int(pmod, "dynamic", 1);
    }

    /* record the (common) type of MIDAS term? */
    type0 = minfo[0].type;
    if (nmidas > 1) {
	for (i=1; i<nmidas; i++) {
	    if (minfo[i].type != type0) {
		mixed = 1;
		break;
	    }
	}
    }
    if (!mixed && type0 > 0) {
	gretl_model_set_int(pmod, "midas_type", type0);
    }	
	
    if (nmidas == 1) {
	/* Record the "gross" MIDAS coefficients, to enable
	   drawing of a plot? We'll do this only if we have
	   a single MIDAS term, which is probably the most
	   most common case. Otherwise it becomes too hard
	   to get the plot right.
	*/
	int nx = list[0] - 1;
	const double *b = pmod->coeff + nx;
	
	add_midas_plot_matrix(pmod, &minfo[0], b);
    }

    if (!err) {
	err = model_add_minfo_array(pmod, minfo, nmidas);
    }

    return err;
}

コード例 #2

ファイル: duration.c プロジェクト: maupatras/gretl

static int 
transcribe_duration_results (MODEL *pmod, duration_info *dinfo, 
			     const DATASET *dset, 
			     int fncount, int grcount, int use_bfgs,
			     int censvar, gretlopt opt)
{
    int np = dinfo->npar;
    int j, v, err = 0;

    pmod->ci = DURATION;

    if (dinfo->dist == DUR_EXPON) {
	pmod->opt |= OPT_E;
    } else if (dinfo->dist == DUR_LOGLOG) {
	pmod->opt |= OPT_L;
    } else if (dinfo->dist == DUR_LOGNORM) {
	pmod->opt |= OPT_Z;
    } else {
	pmod->opt |= OPT_W; /* Weibull */
    }

    if (censvar > 0) {
	gretl_model_set_int(pmod, "cens_var", censvar);
    }

    if (use_bfgs) {
	gretl_model_set_int(pmod, "fncount", fncount);
	gretl_model_set_int(pmod, "grcount", grcount);
    } else {
	gretl_model_set_int(pmod, "iters", fncount);
    } 

    if (!err) {
	err = gretl_model_allocate_param_names(pmod, np);
	if (!err) {
	    for (j=0; j<dinfo->k; j++) {
		v = pmod->list[j+2];
		gretl_model_set_param_name(pmod, j, dset->varname[v]);
	    }
	    if (dinfo->dist != DUR_EXPON) {
		gretl_model_set_param_name(pmod, np-1, "sigma");
	    } 
	}
    }

    if (dinfo->dist == DUR_EXPON) {
	pmod->sigma = 1.0;
    } else {
	pmod->sigma = dinfo->theta[np-1];
    } 

    err = gretl_model_write_coeffs(pmod, dinfo->theta, np);

    if (!err) {
	err = duration_model_add_vcv(pmod, dinfo, dset, opt);
    }

    if (!err) {
	duration_set_predictions(pmod, dinfo, dset, opt);
	pmod->lnL = dinfo->ll;
	mle_criteria(pmod, 0); 
	/* mask invalid statistics */
	pmod->fstt = pmod->chisq = NADBL;
	pmod->rsq = pmod->adjrsq = NADBL;
	pmod->ess = NADBL;
	/* but add overall LR test if possible */
	if (np > 1 + (dinfo->dist != DUR_EXPON)) {
	    duration_overall_LR_test(pmod, dinfo, use_bfgs);
	}
    }

    return err;
}