update project name

DESCRIPTION

@@ -1,5 +1,5 @@
 Type: Package
-Package: meteorit
+Package: meteorits
 Title: Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributions
 Version: 0.1.0
 Authors@R: c(person("Faicel", "Chamroukhi", role = c("aut"),
@@ -30,7 +30,7 @@ LinkingTo:
     Rcpp,
     RcppArmadillo
 Collate:
-    meteorit-package.R
+    meteorits-package.R
     RcppExports.R
     utils.R
     FData.R

NAMESPACE

@@ -16,4 +16,4 @@ exportClasses(StatTMoE)
 import(methods)
 importFrom(Rcpp,sourceCpp)
 importFrom(pracma,fzero)
-useDynLib(meteorit, .registration = TRUE)
+useDynLib(meteorits, .registration = TRUE)

R/RcppExports.R

@@ -2,10 +2,10 @@
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
 IRLS <- function(X, Tau, Gamma, Winit, verbose = FALSE) {
-    .Call(`_meteorit_IRLS`, X, Tau, Gamma, Winit, verbose)
+    .Call(`_meteorits_IRLS`, X, Tau, Gamma, Winit, verbose)
 }
 
 multinomialLogit <- function(W, X, Y, Gamma) {
-    .Call(`_meteorit_multinomialLogit`, W, X, Y, Gamma)
+    .Call(`_meteorits_multinomialLogit`, W, X, Y, Gamma)
 }
 

R/meteorit-package.R → R/meteorits-package.R

@@ -1,6 +1,6 @@
 #' @import methods
 ## usethis namespace: start
-#' @useDynLib meteorit, .registration = TRUE
+#' @useDynLib meteorits, .registration = TRUE
 ## usethis namespace: end
 NULL
 ## usethis namespace: start

README.Rmd

@@ -64,7 +64,7 @@ browseVignettes("MEteorits")
 <details>
   <summary>SNMoE</summary>
 ```{r, message = FALSE}
-library(meteorit)
+library(meteorits)
 
 data("simulatedstructureddata")
 
@@ -89,7 +89,7 @@ snmoe$plot()
 <summary>StMoE</summary>
 
 ```{r, message = FALSE}
-library(meteorit)
+library(meteorits)
 
 data("simulatedstructureddata")
 
@@ -113,7 +113,7 @@ stmoe$plot()
 <details>
 <summary>TMoE</summary>
 ```{r, message = FALSE}
-library(meteorit)
+library(meteorits)
 
 data("simulatedstructureddata")
 

README.md

@@ -1,46 +1,36 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
-
 <!-- badges: start -->
-
 <!-- badges: end -->
-
-## Overview
+Overview
+--------
 
 Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributions
 
-MEteoritS is a toolbox containg several original and flexible
-mixtures-of-experts models to model, cluster and classify heteregenous
-data in many complex situations where the data are distributed according
-non-normal, possibly skewed distributions, and when they might be
-corrupted by atypical observations. The toolbox contains in particular
-sparse mixture-of-experts models for high-dimensional data.
+MEteoritS is a toolbox containg several original and flexible mixtures-of-experts models to model, cluster and classify heteregenous data in many complex situations where the data are distributed according non-normal, possibly skewed distributions, and when they might be corrupted by atypical observations. The toolbox contains in particular sparse mixture-of-experts models for high-dimensional data.
 
 Our (dis-)covered meteorites are for instance the following:
 
-  - NMoE
-  - NNMoE
-  - tMoE
-  - StMoE
-  - SNMoE
-  - RMoE
+-   NMoE
+-   NNMoE
+-   tMoE
+-   StMoE
+-   SNMoE
+-   RMoE
 
-The models and algorithms are developped and written in Matlab by Faicel
-Chamroukhi, and translated and designed into R packages by Florian
-Lecocq, Marius Bartcus and Faicel Chamroukhi.
+The models and algorithms are developped and written in Matlab by Faicel Chamroukhi, and translated and designed into R packages by Florian Lecocq, Marius Bartcus and Faicel Chamroukhi.
 
-## Installation
+Installation
+------------
 
-You can install the development version of STMoE from
-[GitHub](https://github.com/) with:
+You can install the development version of STMoE from [GitHub](https://github.com/) with:
 
 ``` r
 # install.packages("devtools")
 devtools::install_github("fchamroukhi/MEteorits")
 ```
 
-To build *vignettes* for examples of usage, type the command below
-instead:
+To build *vignettes* for examples of usage, type the command below instead:
 
 ``` r
 # install.packages("devtools")
@@ -55,14 +45,13 @@ Use the following command to display vignettes:
 browseVignettes("MEteorits")
 ```
 
-## Usage
+Usage
+-----
 
-<details>
-
-<summary>SNMoE</summary>
+<details> <summary>SNMoE</summary>
 
 ``` r
-library(meteorit)
+library(meteorits)
 
 data("simulatedstructureddata")
 
@@ -82,16 +71,12 @@ snmoe <- emSNMoE(simulatedstructureddata$X, matrix(simulatedstructureddata$Y),
 snmoe$plot()
 ```
 
-<img src="man/figures/README-unnamed-chunk-5-1.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-5-2.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-5-3.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-5-4.png" style="display: block; margin: auto;" />
-
-</details>
-
-<details>
+<img src="man/figures/README-unnamed-chunk-5-1.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-5-2.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-5-3.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-5-4.png" style="display: block; margin: auto;" /> </details>
 
-<summary>TMoE</summary>
+<details> <summary>StMoE</summary>
 
 ``` r
-library(meteorit)
+library(meteorits)
 
 data("simulatedstructureddata")
 
@@ -105,21 +90,18 @@ threshold <- 1e-5
 verbose <- TRUE
 verbose_IRLS <- FALSE
 
-tmoe <- emTMoE(simulatedstructureddata$X, matrix(simulatedstructureddata$Y), K, p, q, n_tries, max_iter, threshold, verbose, verbose_IRLS)
+stmoe <- emStMoE(simulatedstructureddata$X, matrix(simulatedstructureddata$Y), 
+                 K, p, q, n_tries, max_iter, threshold, verbose, verbose_IRLS)
 
-tmoe$plot()
+stmoe$plot()
 ```
 
-<img src="man/figures/README-unnamed-chunk-7-1.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-7-2.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-7-3.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-7-4.png" style="display: block; margin: auto;" />
-
-</details>
+<img src="man/figures/README-unnamed-chunk-6-1.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-6-2.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-6-3.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-6-4.png" style="display: block; margin: auto;" /> </details>
 
-<details>
-
-<summary>StMoE</summary>
+<details> <summary>TMoE</summary>
 
 ``` r
-library(meteorit)
+library(meteorits)
 
 data("simulatedstructureddata")
 
@@ -133,75 +115,28 @@ threshold <- 1e-5
 verbose <- TRUE
 verbose_IRLS <- FALSE
 
-stmoe <- emStMoE(simulatedstructureddata$X, matrix(simulatedstructureddata$Y), 
-                 K, p, q, n_tries, max_iter, threshold, verbose, verbose_IRLS)
+tmoe <- emTMoE(simulatedstructureddata$X, matrix(simulatedstructureddata$Y), K, p, q, n_tries, max_iter, threshold, verbose, verbose_IRLS)
 
-stmoe$plot()
+tmoe$plot()
 ```
 
-<img src="man/figures/README-unnamed-chunk-6-1.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-6-2.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-6-3.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-6-4.png" style="display: block; margin: auto;" />
+<img src="man/figures/README-unnamed-chunk-7-1.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-7-2.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-7-3.png" style="display: block; margin: auto;" /><img src="man/figures/README-unnamed-chunk-7-4.png" style="display: block; margin: auto;" />
 
 </details>
 
-# References
-
-<div id="refs" class="references">
-
-<div id="ref-item1">
-
-Chamroukhi, F, and Bao T Huynh. 2019. “Regularized Maximum Likelihood
-Estimation and Feature Selection in Mixtures-of-Experts Models.”
-*Journal de La Société Française de Statistique* 160(1): 57–85.
-
-</div>
-
-<div id="ref-item2">
-
-Nguyen, Hien D., and F. Chamroukhi. 2018. “Practical and Theoretical
-Aspects of Mixture-of-Experts Modeling: An Overview.” *Wiley
-Interdisciplinary Reviews: Data Mining and Knowledge Discovery*,
-e1246–n/a. <https://doi.org/10.1002/widm.1246>.
-
-</div>
-
-<div id="ref-item3">
-
-Chamroukhi", F. 2017. “Skew T Mixture of Experts.” *Neurocomputing -
-Elsevier* 266: 390–408. <https://chamroukhi.com/papers/STMoE.pdf>.
-
-</div>
-
-<div id="ref-item4">
-
-———. 2016. “Skew-Normal Mixture of Experts.” In *The International Joint
-Conference on Neural Networks (Ijcnn)*.
-<https://chamroukhi.com/papers/Chamroukhi-SNMoE-IJCNN2016.pdf>.
-
-</div>
-
-<div id="ref-item6">
-
-Chamroukhi, F. 2015. “Statistical Learning of Latent Data Models for
-Complex Data Analysis.” Habilitation Thesis (HDR), Université de Toulon.
-<https://chamroukhi.com/Dossier/FChamroukhi-Habilitation.pdf>.
-
-</div>
+References
+==========
 
-<div id="ref-item5">
+Chamroukhi, F, and Bao T Huynh. 2019. “Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models.” *Journal de La Société Française de Statistique* 160(1): 57–85.
 
-———. 2010. “Hidden Process Regression for Curve Modeling, Classification
-and Tracking.” Ph.D. Thesis, Université de Technologie de Compiègne.
-<https://chamroukhi.com/papers/FChamroukhi-Thesis.pdf>.
+Nguyen, Hien D., and F. Chamroukhi. 2018. “Practical and Theoretical Aspects of Mixture-of-Experts Modeling: An Overview.” *Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery*, e1246–n/a. <https://doi.org/10.1002/widm.1246>.
 
-</div>
+Chamroukhi", F. 2017. “Skew T Mixture of Experts.” *Neurocomputing - Elsevier* 266: 390–408. <https://chamroukhi.com/papers/STMoE.pdf>.
 
-<div id="ref-item7">
+———. 2016. “Skew-Normal Mixture of Experts.” In *The International Joint Conference on Neural Networks (Ijcnn)*. <https://chamroukhi.com/papers/Chamroukhi-SNMoE-IJCNN2016.pdf>.
 
-Chamroukhi, F., A. Samé, G. Govaert, and P. Aknin. 2009. “Time Series
-Modeling by a Regression Approach Based on a Latent Process.” *Neural
-Networks* 22 (5-6): 593–602.
-<https://chamroukhi.com/papers/Chamroukhi_Neural_Networks_2009.pdf>.
+Chamroukhi, F. 2015. “Statistical Learning of Latent Data Models for Complex Data Analysis.” Habilitation Thesis (HDR), Université de Toulon. <https://chamroukhi.com/Dossier/FChamroukhi-Habilitation.pdf>.
 
-</div>
+———. 2010. “Hidden Process Regression for Curve Modeling, Classification and Tracking.” Ph.D. Thesis, Université de Technologie de Compiègne. <https://chamroukhi.com/papers/FChamroukhi-Thesis.pdf>.
 
-</div>
+Chamroukhi, F., A. Samé, G. Govaert, and P. Aknin. 2009. “Time Series Modeling by a Regression Approach Based on a Latent Process.” *Neural Networks* 22 (5-6): 593–602. <https://chamroukhi.com/papers/Chamroukhi_Neural_Networks_2009.pdf>.

src/RcppExports.cpp

@@ -8,7 +8,7 @@ using namespace Rcpp;
 
 // IRLS
 List IRLS(arma::mat& X, arma::mat& Tau, arma::mat& Gamma, arma::mat& Winit, bool verbose);
-RcppExport SEXP _meteorit_IRLS(SEXP XSEXP, SEXP TauSEXP, SEXP GammaSEXP, SEXP WinitSEXP, SEXP verboseSEXP) {
+RcppExport SEXP _meteorits_IRLS(SEXP XSEXP, SEXP TauSEXP, SEXP GammaSEXP, SEXP WinitSEXP, SEXP verboseSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
     Rcpp::RNGScope rcpp_rngScope_gen;
@@ -23,7 +23,7 @@ END_RCPP
 }
 // multinomialLogit
 List multinomialLogit(arma::mat& W, arma::mat& X, arma::mat& Y, arma::mat& Gamma);
-RcppExport SEXP _meteorit_multinomialLogit(SEXP WSEXP, SEXP XSEXP, SEXP YSEXP, SEXP GammaSEXP) {
+RcppExport SEXP _meteorits_multinomialLogit(SEXP WSEXP, SEXP XSEXP, SEXP YSEXP, SEXP GammaSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
     Rcpp::RNGScope rcpp_rngScope_gen;
@@ -37,12 +37,12 @@ END_RCPP
 }
 
 static const R_CallMethodDef CallEntries[] = {
-    {"_meteorit_IRLS", (DL_FUNC) &_meteorit_IRLS, 5},
-    {"_meteorit_multinomialLogit", (DL_FUNC) &_meteorit_multinomialLogit, 4},
+    {"_meteorits_IRLS", (DL_FUNC) &_meteorits_IRLS, 5},
+    {"_meteorits_multinomialLogit", (DL_FUNC) &_meteorits_multinomialLogit, 4},
     {NULL, NULL, 0}
 };
 
-RcppExport void R_init_meteorit(DllInfo *dll) {
+RcppExport void R_init_meteorits(DllInfo *dll) {
     R_registerRoutines(dll, NULL, CallEntries, NULL, NULL);
     R_useDynamicSymbols(dll, FALSE);
 }

vignettes/A-quick-tour-of-SNMoE.Rmd

@@ -26,7 +26,7 @@ knit_hooks$set(par = function(before, options, envir)
 ```
 
 ```{r, message = FALSE, echo = FALSE}
-library(meteorit)
+library(meteorits)
 ```
 
 # Introduction

vignettes/A-quick-tour-of-StMoE.Rmd

@@ -26,7 +26,7 @@ knit_hooks$set(par = function(before, options, envir)
 ```
 
 ```{r, message = FALSE, echo = FALSE}
-library(meteorit)
+library(meteorits)
 ```
 
 # Introduction

vignettes/A-quick-tour-of-tMoE.Rmd

@@ -26,7 +26,7 @@ knit_hooks$set(par = function(before, options, envir)
 ```
 
 ```{r, message = FALSE, echo = FALSE}
-library(meteorit)
+library(meteorits)
 ```
 
 # Introduction