/* nag_regsn_mult_linear_tran_model (g02dkc) Example Program. * * Copyright 1991 Numerical Algorithms Group. * * Mark 2, 1991. * Mark 8 revised, 2004. */ #include #include #include #include #define X(I, J) x[(I) *tdx + J] #define C(I, J) c[(I) *tdc + J] #define Q(I, J) q[(I) *tdq + J] int main(void) { Integer exit_status = 0, i, iconst, ip, j, m, n, rank, *sx = 0, tdc, tdq, tdx; double df, rss, tol; double *b = 0, *c = 0, *com_ar = 0, *cov = 0, *h = 0, *p = 0; double *q = 0, *res = 0, *se = 0, *wt = 0, *wtptr, *x = 0, *y = 0; char nag_enum_arg[40]; Nag_Boolean svd, weight; Nag_IncludeMean mean; NagError fail; INIT_FAIL(fail); printf("nag_regsn_mult_linear_tran_model (g02dkc) Example Program " "Results\n"); /* Skip heading in data file */ scanf("%*[^\n]"); scanf("%ld %ld", &n, &m); scanf(" %s", nag_enum_arg); /* nag_enum_name_to_value(x04nac). * Converts NAG enum member name to value */ weight = (Nag_Boolean) nag_enum_name_to_value(nag_enum_arg); scanf(" %s", nag_enum_arg); mean = (Nag_IncludeMean) nag_enum_name_to_value(nag_enum_arg); if (n >= 2 && m >= 1) { if (!(h = NAG_ALLOC(n, double)) || !(res = NAG_ALLOC(n, double)) || !(wt = NAG_ALLOC(n, double)) || !(x = NAG_ALLOC(n*m, double)) || !(y = NAG_ALLOC(n, double)) || !(sx = NAG_ALLOC(m, Integer))) { printf("Allocation failure\n"); exit_status = -1; goto END; } tdx = m; } else { printf("Invalid n.\n"); exit_status = 1; return exit_status; } if (weight) { wtptr = wt; for (i = 0; i < n; i++) { for (j = 0; j < m; j++) scanf("%lf", &X(i, j)); scanf("%lf%lf", &y[i], &wt[i]); } } else { wtptr = (double *) 0; for (i = 0; i < n; i++) { for (j = 0; j < m; j++) scanf("%lf", &X(i, j)); scanf("%lf", &y[i]); } } for (j = 0; j < m; j++) scanf("%ld", &sx[j]); scanf("%ld", &ip); if (!(b = NAG_ALLOC(ip, double)) || !(c = NAG_ALLOC((ip)*(ip), double)) || !(cov = NAG_ALLOC(ip*(ip+1)/2, double)) || !(p = NAG_ALLOC(ip*(ip+2), double)) || !(q = NAG_ALLOC(n*(ip+1), double)) || !(se = NAG_ALLOC(ip, double)) || !(com_ar = NAG_ALLOC(4*ip*ip+5*(ip-1), double))) { printf("Allocation failure\n"); exit_status = -1; goto END; } tdq = ip+1; tdc = ip; /* Set tolerance */ tol = 0.00001e0; /* Find initial estimates using nag_regsn_mult_linear (g02dac) */ /* nag_regsn_mult_linear (g02dac). * Fits a general (multiple) linear regression model */ nag_regsn_mult_linear(mean, n, x, tdx, m, sx, ip, y, wtptr, &rss, &df, b, se, cov, res, h, q, tdq, &svd, &rank, p, tol, com_ar, &fail); if (fail.code != NE_NOERROR) { printf("Error from nag_regsn_mult_linear (g02dac).\n%s\n", fail.message); exit_status = 1; goto END; } printf("Estimates from g02dac\n\n"); printf("Residual sum of squares = %13.4e\n", rss); printf("Degrees of freedom = %3.1f\n\n", df); printf("Variable Parameter estimate Standard error\n\n"); for (j = 0; j < ip; j++) printf("%6ld%20.4e%20.4e\n", j+1, b[j], se[j]); printf("\n"); /* * Input constraints and call nag_regsn_mult_linear_tran_model (g02dkc) */ iconst = ip - rank; for (i = 0; i < ip; ++i) for (j = 0; j < iconst; ++j) scanf("%lf", &C(i, j)); /* nag_regsn_mult_linear_tran_model (g02dkc). * Estimates of parameters of a general linear regression * model for given constraints */ nag_regsn_mult_linear_tran_model(ip, iconst, p, c, tdc, b, rss, df, se, cov, &fail); if (fail.code != NE_NOERROR) { printf( "Error from nag_regsn_mult_linear_tran_model (g02dkc).\n%s\n", fail.message); exit_status = 1; goto END; } printf("\n"); printf( "Estimates from nag_regsn_mult_linear_tran_model (g02dkc) using " "constraints\n\n"); printf("Variable Parameter estimate Standard error\n\n"); for (j = 0; j < ip; j++) printf("%6ld%20.4e%20.4e\n", j+1, b[j], se[j]); printf("\n"); END: if (h) NAG_FREE(h); if (res) NAG_FREE(res); if (wt) NAG_FREE(wt); if (x) NAG_FREE(x); if (y) NAG_FREE(y); if (sx) NAG_FREE(sx); if (b) NAG_FREE(b); if (c) NAG_FREE(c); if (cov) NAG_FREE(cov); if (p) NAG_FREE(p); if (q) NAG_FREE(q); if (se) NAG_FREE(se); if (com_ar) NAG_FREE(com_ar); return exit_status; }