1# Generated by using Rcpp::compileAttributes() -> do not edit by hand
2# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
3
4bayesBLP_rcpp_loop <- function(IV, X, Z, share, J, T, v, R, sigmasqR, A, theta_hat, deltabar, Ad, nu0, s0_sq, VOmega, ssq, cand_cov, theta_bar_initial, r_initial, tau_sq_initial, Omega_initial, delta_initial, tol, keep, nprint) {
5    .Call('_bayesm_bayesBLP_rcpp_loop', PACKAGE = 'bayesm', IV, X, Z, share, J, T, v, R, sigmasqR, A, theta_hat, deltabar, Ad, nu0, s0_sq, VOmega, ssq, cand_cov, theta_bar_initial, r_initial, tau_sq_initial, Omega_initial, delta_initial, tol, keep, nprint)
6}
7
8breg <- function(y, X, betabar, A) {
9    .Call('_bayesm_breg', PACKAGE = 'bayesm', y, X, betabar, A)
10}
11
12cgetC <- function(e, k) {
13    .Call('_bayesm_cgetC', PACKAGE = 'bayesm', e, k)
14}
15
16clusterMix_rcpp_loop <- function(zdraw, cutoff, SILENT, nprint) {
17    .Call('_bayesm_clusterMix_rcpp_loop', PACKAGE = 'bayesm', zdraw, cutoff, SILENT, nprint)
18}
19
20ghkvec <- function(L, trunpt, above, r, HALTON = TRUE, pn = as.integer( c(0))) {
21    .Call('_bayesm_ghkvec', PACKAGE = 'bayesm', L, trunpt, above, r, HALTON, pn)
22}
23
24llmnl <- function(beta, y, X) {
25    .Call('_bayesm_llmnl', PACKAGE = 'bayesm', beta, y, X)
26}
27
28lndIChisq <- function(nu, ssq, X) {
29    .Call('_bayesm_lndIChisq', PACKAGE = 'bayesm', nu, ssq, X)
30}
31
32lndIWishart <- function(nu, V, IW) {
33    .Call('_bayesm_lndIWishart', PACKAGE = 'bayesm', nu, V, IW)
34}
35
36lndMvn <- function(x, mu, rooti) {
37    .Call('_bayesm_lndMvn', PACKAGE = 'bayesm', x, mu, rooti)
38}
39
40lndMvst <- function(x, nu, mu, rooti, NORMC = FALSE) {
41    .Call('_bayesm_lndMvst', PACKAGE = 'bayesm', x, nu, mu, rooti, NORMC)
42}
43
44rDPGibbs_rcpp_loop <- function(R, keep, nprint, y, lambda_hyper, SCALE, maxuniq, PrioralphaList, gridsize, BayesmConstantA, BayesmConstantnuInc, BayesmConstantDPalpha) {
45    .Call('_bayesm_rDPGibbs_rcpp_loop', PACKAGE = 'bayesm', R, keep, nprint, y, lambda_hyper, SCALE, maxuniq, PrioralphaList, gridsize, BayesmConstantA, BayesmConstantnuInc, BayesmConstantDPalpha)
46}
47
48rbprobitGibbs_rcpp_loop <- function(y, X, Abetabar, root, beta, sigma, trunpt, above, R, keep, nprint) {
49    .Call('_bayesm_rbprobitGibbs_rcpp_loop', PACKAGE = 'bayesm', y, X, Abetabar, root, beta, sigma, trunpt, above, R, keep, nprint)
50}
51
52rdirichlet <- function(alpha) {
53    .Call('_bayesm_rdirichlet', PACKAGE = 'bayesm', alpha)
54}
55
56rhierLinearMixture_rcpp_loop <- function(regdata, Z, deltabar, Ad, mubar, Amu, nu, V, nu_e, ssq, R, keep, nprint, drawdelta, olddelta, a, oldprob, ind, tau) {
57    .Call('_bayesm_rhierLinearMixture_rcpp_loop', PACKAGE = 'bayesm', regdata, Z, deltabar, Ad, mubar, Amu, nu, V, nu_e, ssq, R, keep, nprint, drawdelta, olddelta, a, oldprob, ind, tau)
58}
59
60rhierLinearModel_rcpp_loop <- function(regdata, Z, Deltabar, A, nu, V, nu_e, ssq, tau, Delta, Vbeta, R, keep, nprint) {
61    .Call('_bayesm_rhierLinearModel_rcpp_loop', PACKAGE = 'bayesm', regdata, Z, Deltabar, A, nu, V, nu_e, ssq, tau, Delta, Vbeta, R, keep, nprint)
62}
63
64rhierMnlDP_rcpp_loop <- function(R, keep, nprint, lgtdata, Z, deltabar, Ad, PrioralphaList, lambda_hyper, drawdelta, nvar, oldbetas, s, maxuniq, gridsize, BayesmConstantA, BayesmConstantnuInc, BayesmConstantDPalpha) {
65    .Call('_bayesm_rhierMnlDP_rcpp_loop', PACKAGE = 'bayesm', R, keep, nprint, lgtdata, Z, deltabar, Ad, PrioralphaList, lambda_hyper, drawdelta, nvar, oldbetas, s, maxuniq, gridsize, BayesmConstantA, BayesmConstantnuInc, BayesmConstantDPalpha)
66}
67
68llmnl_con <- function(betastar, y, X, SignRes = as.numeric( c(0))) {
69    .Call('_bayesm_llmnl_con', PACKAGE = 'bayesm', betastar, y, X, SignRes)
70}
71
72rhierMnlRwMixture_rcpp_loop <- function(lgtdata, Z, deltabar, Ad, mubar, Amu, nu, V, s, R, keep, nprint, drawdelta, olddelta, a, oldprob, oldbetas, ind, SignRes) {
73    .Call('_bayesm_rhierMnlRwMixture_rcpp_loop', PACKAGE = 'bayesm', lgtdata, Z, deltabar, Ad, mubar, Amu, nu, V, s, R, keep, nprint, drawdelta, olddelta, a, oldprob, oldbetas, ind, SignRes)
74}
75
76rhierNegbinRw_rcpp_loop <- function(regdata, hessdata, Z, Beta, Delta, Deltabar, Adelta, nu, V, a, b, R, keep, sbeta, alphacroot, nprint, rootA, alpha, fixalpha) {
77    .Call('_bayesm_rhierNegbinRw_rcpp_loop', PACKAGE = 'bayesm', regdata, hessdata, Z, Beta, Delta, Deltabar, Adelta, nu, V, a, b, R, keep, sbeta, alphacroot, nprint, rootA, alpha, fixalpha)
78}
79
80rivDP_rcpp_loop <- function(R, keep, nprint, dimd, mbg, Abg, md, Ad, y, isgamma, z, x, w, delta, PrioralphaList, gridsize, SCALE, maxuniq, scalex, scaley, lambda_hyper, BayesmConstantA, BayesmConstantnu) {
81    .Call('_bayesm_rivDP_rcpp_loop', PACKAGE = 'bayesm', R, keep, nprint, dimd, mbg, Abg, md, Ad, y, isgamma, z, x, w, delta, PrioralphaList, gridsize, SCALE, maxuniq, scalex, scaley, lambda_hyper, BayesmConstantA, BayesmConstantnu)
82}
83
84rivGibbs_rcpp_loop <- function(y, x, z, w, mbg, Abg, md, Ad, V, nu, R, keep, nprint) {
85    .Call('_bayesm_rivGibbs_rcpp_loop', PACKAGE = 'bayesm', y, x, z, w, mbg, Abg, md, Ad, V, nu, R, keep, nprint)
86}
87
88rmixGibbs <- function(y, Bbar, A, nu, V, a, p, z) {
89    .Call('_bayesm_rmixGibbs', PACKAGE = 'bayesm', y, Bbar, A, nu, V, a, p, z)
90}
91
92rmixture <- function(n, pvec, comps) {
93    .Call('_bayesm_rmixture', PACKAGE = 'bayesm', n, pvec, comps)
94}
95
96rmnlIndepMetrop_rcpp_loop <- function(R, keep, nu, betastar, root, y, X, betabar, rootpi, rooti, oldlimp, oldlpost, nprint) {
97    .Call('_bayesm_rmnlIndepMetrop_rcpp_loop', PACKAGE = 'bayesm', R, keep, nu, betastar, root, y, X, betabar, rootpi, rooti, oldlimp, oldlpost, nprint)
98}
99
100rmnpGibbs_rcpp_loop <- function(R, keep, nprint, pm1, y, X, beta0, sigma0, V, nu, betabar, A) {
101    .Call('_bayesm_rmnpGibbs_rcpp_loop', PACKAGE = 'bayesm', R, keep, nprint, pm1, y, X, beta0, sigma0, V, nu, betabar, A)
102}
103
104rmultireg <- function(Y, X, Bbar, A, nu, V) {
105    .Call('_bayesm_rmultireg', PACKAGE = 'bayesm', Y, X, Bbar, A, nu, V)
106}
107
108rmvpGibbs_rcpp_loop <- function(R, keep, nprint, p, y, X, beta0, sigma0, V, nu, betabar, A) {
109    .Call('_bayesm_rmvpGibbs_rcpp_loop', PACKAGE = 'bayesm', R, keep, nprint, p, y, X, beta0, sigma0, V, nu, betabar, A)
110}
111
112rmvst <- function(nu, mu, root) {
113    .Call('_bayesm_rmvst', PACKAGE = 'bayesm', nu, mu, root)
114}
115
116rnegbinRw_rcpp_loop <- function(y, X, betabar, rootA, a, b, beta, alpha, fixalpha, betaroot, alphacroot, R, keep, nprint) {
117    .Call('_bayesm_rnegbinRw_rcpp_loop', PACKAGE = 'bayesm', y, X, betabar, rootA, a, b, beta, alpha, fixalpha, betaroot, alphacroot, R, keep, nprint)
118}
119
120rnmixGibbs_rcpp_loop <- function(y, Mubar, A, nu, V, a, p, z, R, keep, nprint) {
121    .Call('_bayesm_rnmixGibbs_rcpp_loop', PACKAGE = 'bayesm', y, Mubar, A, nu, V, a, p, z, R, keep, nprint)
122}
123
124rordprobitGibbs_rcpp_loop <- function(y, X, k, A, betabar, Ad, s, inc_root, dstarbar, betahat, R, keep, nprint) {
125    .Call('_bayesm_rordprobitGibbs_rcpp_loop', PACKAGE = 'bayesm', y, X, k, A, betabar, Ad, s, inc_root, dstarbar, betahat, R, keep, nprint)
126}
127
128rscaleUsage_rcpp_loop <- function(k, x, p, n, R, keep, ndghk, nprint, y, mu, Sigma, tau, sigma, Lambda, e, domu, doSigma, dosigma, dotau, doLambda, doe, nu, V, mubar, Am, gsigma, gl11, gl22, gl12, nuL, VL, ge) {
129    .Call('_bayesm_rscaleUsage_rcpp_loop', PACKAGE = 'bayesm', k, x, p, n, R, keep, ndghk, nprint, y, mu, Sigma, tau, sigma, Lambda, e, domu, doSigma, dosigma, dotau, doLambda, doe, nu, V, mubar, Am, gsigma, gl11, gl22, gl12, nuL, VL, ge)
130}
131
132rsurGibbs_rcpp_loop <- function(regdata, indreg, cumnk, nk, XspXs, Sigmainv, A, Abetabar, nu, V, nvar, E, Y, R, keep, nprint) {
133    .Call('_bayesm_rsurGibbs_rcpp_loop', PACKAGE = 'bayesm', regdata, indreg, cumnk, nk, XspXs, Sigmainv, A, Abetabar, nu, V, nvar, E, Y, R, keep, nprint)
134}
135
136rtrun <- function(mu, sigma, a, b) {
137    .Call('_bayesm_rtrun', PACKAGE = 'bayesm', mu, sigma, a, b)
138}
139
140runiregGibbs_rcpp_loop <- function(y, X, betabar, A, nu, ssq, sigmasq, R, keep, nprint) {
141    .Call('_bayesm_runiregGibbs_rcpp_loop', PACKAGE = 'bayesm', y, X, betabar, A, nu, ssq, sigmasq, R, keep, nprint)
142}
143
144runireg_rcpp_loop <- function(y, X, betabar, A, nu, ssq, R, keep, nprint) {
145    .Call('_bayesm_runireg_rcpp_loop', PACKAGE = 'bayesm', y, X, betabar, A, nu, ssq, R, keep, nprint)
146}
147
148rwishart <- function(nu, V) {
149    .Call('_bayesm_rwishart', PACKAGE = 'bayesm', nu, V)
150}
151
152callroot <- function(c1, c2, tol, iterlim) {
153    .Call('_bayesm_callroot', PACKAGE = 'bayesm', c1, c2, tol, iterlim)
154}
155
156