translated the c code to c++

.gitignore

@@ -40,3 +40,8 @@ vignettes/*.pdf
 *.o
 *.so
 *.Rproj
+tests/.DS_Store
+src/TMB/.DS_Store
+src/.DS_Store
+.github/.DS_Store
+.DS_Store

DESCRIPTION

@@ -1,17 +1,17 @@
 Package: tsdistributions
 Type: Package
 Title: Location Scale Standardized Distributions
-Version: 1.0.1
+Version: 1.0.2
 Authors@R: c(person("Alexios", "Galanos", role = c("aut", "cre","cph"), email = "alexios@4dscape.com"))
 Maintainer: Alexios Galanos <alexios@4dscape.com>
 Depends: R (>= 3.5.0), methods, tsmethods
-LinkingTo: TMB, RcppEigen
-Imports: TMB (>= 1.7.20), Rdpack, GeneralizedHyperbolic, KernSmooth, SkewHyperbolic, mev, stats, utils, data.table, zoo, Rsolnp, sandwich, future.apply, future, progressr
+LinkingTo: Rcpp, TMB, RcppEigen
+Imports: Rcpp, TMB (>= 1.7.20), Rdpack, GeneralizedHyperbolic, KernSmooth, SkewHyperbolic, mev, stats, utils, data.table, zoo, Rsolnp, sandwich, future.apply, future, progressr
 Description: Location-Scale based distributions parameterized in terms of mean, standard deviation, skew and shape parameters and estimation using automatic differentiation. Distributions include the Normal, Student and GED as well as their skewed variants ('Fernandez and Steel'), the 'Johnson SU', and the Generalized Hyperbolic. Also included is the semi-parametric piece wise distribution ('spd') with Pareto tails and kernel interior.
 License: GPL-2
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 VignetteBuilder: knitr
 RdMacros: Rdpack
 URL: https://www.nopredict.com/packages/tsdistributions, https://github.com/tsmodels/tsdistributions

NAMESPACE

@@ -28,6 +28,7 @@ export(ddist)
 export(dged)
 export(dgh)
 export(dghst)
+export(dghyp)
 export(distribution_bounds)
 export(distribution_modelspec)
 export(djsu)
@@ -45,6 +46,7 @@ export(pdist)
 export(pged)
 export(pgh)
 export(pghst)
+export(pghyp)
 export(pjsu)
 export(pnig)
 export(psged)
@@ -56,6 +58,7 @@ export(qdist)
 export(qged)
 export(qgh)
 export(qghst)
+export(qghyp)
 export(qjsu)
 export(qnig)
 export(qsged)
@@ -67,6 +70,7 @@ export(rdist)
 export(rged)
 export(rgh)
 export(rghst)
+export(rghyp)
 export(rjsu)
 export(rnig)
 export(rsged)
@@ -79,8 +83,9 @@ import(data.table)
 import(methods)
 import(tsmethods)
 importFrom(GeneralizedHyperbolic,ghypMom)
-importFrom(GeneralizedHyperbolic,rghyp)
 importFrom(KernSmooth,bkde)
+importFrom(Rcpp,evalCpp)
+importFrom(Rcpp,sourceCpp)
 importFrom(Rdpack,reprompt)
 importFrom(Rsolnp,solnp)
 importFrom(SkewHyperbolic,pskewhyp)

NEWS.md

@@ -1,3 +1,9 @@
+# tsdistributions 1.0.2
+
+* Replaced PI with M_PI to pass strict header checks
+* Translated the distribution.c c functions to Rcpp.
+
+
 # tsdistributions 1.0.1
 
 * Added the semi-parametric piece-wise distribution (`spd`). As this is a special

R/RcppExports.R

@@ -0,0 +1,127 @@
+# Generated by using Rcpp::compileAttributes() -> do not edit by hand
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+c_dghst <- function(x, mu, sigma, skew, shape, logr) {
+    .Call(`_tsdistributions_c_dghst`, x, mu, sigma, skew, shape, logr)
+}
+
+c_rghst <- function(n, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_rghst`, n, mu, sigma, skew, shape)
+}
+
+c_dghyp <- function(x, alpha, beta, delta, mu, lambda, logr) {
+    .Call(`_tsdistributions_c_dghyp`, x, alpha, beta, delta, mu, lambda, logr)
+}
+
+c_dgh <- function(x, mu, sigma, skew, shape, lambda, logr) {
+    .Call(`_tsdistributions_c_dgh`, x, mu, sigma, skew, shape, lambda, logr)
+}
+
+c_dnig <- function(x, mu, sigma, skew, shape, logr) {
+    .Call(`_tsdistributions_c_dnig`, x, mu, sigma, skew, shape, logr)
+}
+
+c_rstd <- function(n, mu, sigma, shape) {
+    .Call(`_tsdistributions_c_rstd`, n, mu, sigma, shape)
+}
+
+c_dstd <- function(x, mu, sigma, shape, logr) {
+    .Call(`_tsdistributions_c_dstd`, x, mu, sigma, shape, logr)
+}
+
+c_pstd <- function(q, mu, sigma, shape) {
+    .Call(`_tsdistributions_c_pstd`, q, mu, sigma, shape)
+}
+
+c_qstd <- function(p, mu, sigma, shape) {
+    .Call(`_tsdistributions_c_qstd`, p, mu, sigma, shape)
+}
+
+c_rsstd <- function(n, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_rsstd`, n, mu, sigma, skew, shape)
+}
+
+c_dsstd <- function(x, mu, sigma, skew, shape, logr) {
+    .Call(`_tsdistributions_c_dsstd`, x, mu, sigma, skew, shape, logr)
+}
+
+c_psstd <- function(q, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_psstd`, q, mu, sigma, skew, shape)
+}
+
+c_qsstd <- function(p, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_qsstd`, p, mu, sigma, skew, shape)
+}
+
+c_djsu <- function(x, mu, sigma, skew, shape, logr) {
+    .Call(`_tsdistributions_c_djsu`, x, mu, sigma, skew, shape, logr)
+}
+
+c_qjsu <- function(p, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_qjsu`, p, mu, sigma, skew, shape)
+}
+
+c_pjsu <- function(q, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_pjsu`, q, mu, sigma, skew, shape)
+}
+
+c_rjsu <- function(n, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_rjsu`, n, mu, sigma, skew, shape)
+}
+
+c_rsnorm <- function(n, mu, sigma, skew) {
+    .Call(`_tsdistributions_c_rsnorm`, n, mu, sigma, skew)
+}
+
+c_dsnorm <- function(x, mu, sigma, skew, logr) {
+    .Call(`_tsdistributions_c_dsnorm`, x, mu, sigma, skew, logr)
+}
+
+c_psnorm <- function(q, mu, sigma, skew) {
+    .Call(`_tsdistributions_c_psnorm`, q, mu, sigma, skew)
+}
+
+c_qsnorm <- function(p, mu, sigma, skew) {
+    .Call(`_tsdistributions_c_qsnorm`, p, mu, sigma, skew)
+}
+
+c_rged <- function(n, mu, sigma, shape) {
+    .Call(`_tsdistributions_c_rged`, n, mu, sigma, shape)
+}
+
+c_dged <- function(x, mu, sigma, shape, logr) {
+    .Call(`_tsdistributions_c_dged`, x, mu, sigma, shape, logr)
+}
+
+c_pged <- function(q, mu, sigma, shape) {
+    .Call(`_tsdistributions_c_pged`, q, mu, sigma, shape)
+}
+
+c_qged <- function(p, mu, sigma, shape) {
+    .Call(`_tsdistributions_c_qged`, p, mu, sigma, shape)
+}
+
+c_rsged <- function(n, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_rsged`, n, mu, sigma, skew, shape)
+}
+
+c_dsged <- function(x, mu, sigma, skew, shape, logr) {
+    .Call(`_tsdistributions_c_dsged`, x, mu, sigma, skew, shape, logr)
+}
+
+c_psged <- function(q, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_psged`, q, mu, sigma, skew, shape)
+}
+
+c_qsged <- function(p, mu, sigma, skew, shape) {
+    .Call(`_tsdistributions_c_qsged`, p, mu, sigma, skew, shape)
+}
+
+c_dhyp <- function(x, mu, sigma, skew, shape, logr) {
+    .Call(`_tsdistributions_c_dhyp`, x, mu, sigma, skew, shape, logr)
+}
+
+c_rghyp <- function(n, mu = 0, delta = 1, alpha = 1, beta = 0, lambda = 1) {
+    .Call(`_tsdistributions_c_rghyp`, n, mu, delta, alpha, beta, lambda)
+}
+