remove revdepcheck folder, remove problems with documentation, updated cran-comments and NEWS and DESCRIPTION

Author: lionelvoirol

DESCRIPTION

@@ -1,8 +1,7 @@
 Package: simts
 Type: Package
 Title: Time Series Analysis Tools
-Version: 0.2.2
-Date: 2023-09-29
+Version: 0.2.3
 LazyData: true
 Authors@R: c(
     person("Stéphane", "Guerrier", email = "stef.guerrier@gmail.com", role = c("aut","cre","cph")),

NEWS.md

@@ -1,3 +1,9 @@
+# simts 0.2.3
+
+- solved problems related to documentation with itemize tags in return tags that were creating problems on check
+- moved from arma::is_finite to std::isfinite in file src/rtoarmadillo.cpp
+
+
 # simts 0.2.0
 
 ## Features

R/RcppExports.R

@@ -1043,14 +1043,14 @@ code_zero <- function(theta) {
 #' @details
 #' If type = "imu" or "ssm", then parameter vector should indicate the characters of the models that compose the latent or state-space model.
 #' The model options are:
-#' \itemize{
+#' \describe{
 #'   \item{"AR1"}{a first order autoregressive process with parameters \eqn{(\phi,\sigma^2)}{phi, sigma^2}}
 #'   \item{"ARMA"}{an autoregressive moving average process with parameters \eqn{(\phi _p, \theta _q, \sigma^2)}{phi[p], theta[q], sigma^2}}
 #'   \item{"DR"}{a drift with parameter \eqn{\omega}{omega}}
 #'   \item{"QN"}{a quantization noise process with parameter \eqn{Q}}
 #'   \item{"RW"}{a random walk process with parameter \eqn{\sigma^2}{sigma^2}}
 #'   \item{"WN"}{a white noise process with parameter \eqn{\sigma^2}{sigma^2}}
-#' }
+#'   }
 #' If model_type = "imu" or type = "ssm" then
 #' starting values pass through an initial bootstrap and pseudo-optimization before being passed to the GMWM optimization.
 #' If robust = TRUE the function takes the robust estimate of the wavelet variance to be used in the GMWM estimation procedure.
@@ -2191,11 +2191,9 @@ wave_variance <- function(signal_modwt_bw, robust = FALSE, eff = 0.6) {
 #' @param alpha            A \code{double} that indicates the \eqn{\left(1-p\right)*\alpha}{(1-p)*alpha} confidence level 
 #' @param ci_type          A \code{String} indicating the confidence interval being calculated. Valid value: "eta3"
 #' @return A \code{mat} with the structure:
-#' \itemize{
 #'   \item{"variance"}{Wavelet Variance}
 #'   \item{"low"}{Lower CI}
 #'   \item{"high"}{Upper CI}
-#' }
 #' @keywords internal
 #' @details 
 #' This function does the heavy lifting with the signal_modwt_bw
@@ -2213,11 +2211,9 @@ wvar_cpp <- function(signal_modwt_bw, robust, eff, alpha, ci_type) {
 #' @param strWavelet A \code{string} indicating the type of wave filter to be applied. Must be "haar"
 #' @param decomp     A \code{string} indicating whether to use "modwt" or "dwt" decomp
 #' @return A \code{mat} with the structure:
-#' \itemize{
 #'   \item{"variance"}{Wavelet Variance}
 #'   \item{"low"}{Lower CI}
 #'   \item{"high"}{Upper CI}
-#' }
 #' @keywords internal
 #' @details 
 #' This function powers the wvar object. It is also extendable...

R/gmwm.r

@@ -282,7 +282,6 @@ gmwm = function(model, data, model.type="imu", compute.v="auto",
 #' @param model   A \code{ts.model} object containing one of the allowed models
 #' @param ...     Additional parameters (not used)
 #' @return A \code{gmwm} object with the structure:
-#' \itemize{
 #'  \item{estimate}{Estimated Parameters Values from the GMWM Procedure}
 #'  \item{init.guess}{Initial Starting Values given to the Optimization Algorithm}
 #'  \item{wv.empir}{The data's empirical wavelet variance}
@@ -311,7 +310,6 @@ gmwm = function(model, data, model.type="imu", compute.v="auto",
 #'  \item{starting}{Indicates whether the procedure used the initial guessing approach}
 #'  \item{seed}{Randomization seed used to generate the guessing values}
 #'  \item{freq}{Frequency of data}
-#' }
 update.gmwm = function(object, model, ...){
   # Do we have a valid model?
   if(!is.ts.model(model)){
@@ -428,7 +426,6 @@ update.gmwm = function(object, model, ...){
 #' ability to interpret with respect to \code{freq}, then use
 #' \code{AR1} terms.
 #' @return A \code{gmwm} object with the structure:
-#' \itemize{
 #'  \item{estimate}{Estimated Parameters Values from the GMWM Procedure}
 #'  \item{init.guess}{Initial Starting Values given to the Optimization Algorithm}
 #'  \item{wv.empir}{The data's empirical wavelet variance}
@@ -457,7 +454,6 @@ update.gmwm = function(object, model, ...){
 #'  \item{starting}{Indicates whether the procedure used the initial guessing approach}
 #'  \item{seed}{Randomization seed used to generate the guessing values}
 #'  \item{freq}{Frequency of data}
-#' }
 gmwm_imu = function(model, data, compute.v = "fast", robust = F, eff = 0.6, ...){
 
   x = gmwm(model = model,
@@ -537,7 +533,6 @@ print.gmwm = function(x, ...){
 #' @param B            An \code{int} that indicates how many bootstraps should be performed.
 #' @param ...          Other arguments passed to specific methods
 #' @return A \code{summary.gmwm} object with:
-#' \itemize{
 #'  \item{estimate}{Estimated Theta Values}
 #'  \item{testinfo}{Goodness of Fit Information}
 #'  \item{inference}{Inference performed? T/F}
@@ -549,7 +544,6 @@ print.gmwm = function(x, ...){
 #'  \item{seed}{Seed used during guessing / bootstrapping}
 #'  \item{obj.fun}{Value of obj.fun at minimized theta}
 #'  \item{N}{Length of Time Series}
-#' }
 #' @export
 #' @author JJB
 summary.gmwm = function(object, inference = NULL,
@@ -700,11 +694,9 @@ print.summary.gmwm = function(x, ...){
 #' @param n.ahead      Number of observations to forecast
 #' @param ...          Additional parameters passed to ARIMA Predict
 #' @return A \code{predict.gmwm} object with:
-#' \itemize{
 #' \item{pred}{Predictions}
 #' \item{se}{Standard Errors}
 #' \item{resid}{Residuals from ARIMA ML Fit}
-#' }
 #' @export
 predict.gmwm = function(object, data.in.gmwm, n.ahead = 1, ...){
 

R/ts.model.R

@@ -1041,14 +1041,12 @@ simplified_print_SARIMA = function(p, i, q, P, si, Q, s){
 #' @param x A \code{ts.model} object
 #' @param y A \code{ts.model} object
 #' @return An S3 object with called ts.model with the following structure:
-#' \itemize{
 #'  \item{process.desc}{combined x, y desc}
 #'  \item{theta}{combined x, y theta}
 #'  \item{plength}{Number of Parameters}
 #'  \item{desc}{Add process to queue e.g. c("AR1","WN")}
 #'  \item{obj.desc}{Depth of Parameters e.g. list(1, c(1,1), c(length(ar),length(ma),1) )}
 #'  \item{starting}{Guess Starting values? TRUE or FALSE (e.g. specified value)}
-#' }
 #' @author James Balamuta
 #' @export
 #' @keywords internal

README.Rmd

@@ -20,7 +20,7 @@ library(simts)
 [![CRAN](http://www.r-pkg.org/badges/version/simts)](https://cran.r-project.org/package=simts)
 [![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/simts)](https://www.r-pkg.org/pkg/simts)
 [![CRAN RStudio mirror downloads](https://cranlogs.r-pkg.org/badges/grand-total/simts)](https://www.r-pkg.org/pkg/simts)
-[![Last-changedate](https://img.shields.io/badge/last%20change-`r gsub('-', '--', Sys.Date())`-green.svg)](https://github.com/SMAC-Group/simts)
+![](https://img.shields.io/github/last-commit/SMAC-Group/simts) 
 
 # `simts` Overview <a href="https://smac-group.com/"><img src="man/figures/logo.png" align="right" style="width: 20%; height: 20%"/></a>
 

README.md

@@ -10,7 +10,8 @@ version](https://img.shields.io/badge/R%3E%3D-3.4.0-6666ff.svg)](https://cran.r-
 downloads](http://cranlogs.r-pkg.org/badges/simts)](https://www.r-pkg.org/pkg/simts)
 [![CRAN RStudio mirror
 downloads](https://cranlogs.r-pkg.org/badges/grand-total/simts)](https://www.r-pkg.org/pkg/simts)
-![](https://img.shields.io/github/last-commit/SMAC-Group/gmwmx) 
+[![Last-changedate](https://img.shields.io/badge/last%20change-2025--10--07-green.svg)](https://github.com/SMAC-Group/simts)
+
 # `simts` Overview <a href="https://smac-group.com/"><img src="man/figures/logo.png" align="right" style="width: 20%; height: 20%"/></a>
 
 The Time Series Tools (`simts`) R package provides a series of tools to
@@ -21,17 +22,17 @@ R”](https://smac-group.github.io/ts/) but can obviously be used for time
 series analysis in general. More specifically, the package provides
 tools with the following features:
 
--   Simulation of time series from SARIMA models to various state-space
-    models that can be expressed as latent time series processes.
--   Visualization of time series data with user specifications.
--   Specific simulation and visualization tools for latent time series
-    models.
--   Easy-to-use functions to estimate and infer on the parameters of
-    time series models through different methods (standard and robust).
--   Diagnostic and statistical tools to assess goodness of fit and
-    select the best model for the data.
--   Estimating and plotting tools to deliver point forecasts and
-    confidence intervals.
+- Simulation of time series from SARIMA models to various state-space
+  models that can be expressed as latent time series processes.
+- Visualization of time series data with user specifications.
+- Specific simulation and visualization tools for latent time series
+  models.
+- Easy-to-use functions to estimate and infer on the parameters of time
+  series models through different methods (standard and robust).
+- Diagnostic and statistical tools to assess goodness of fit and select
+  the best model for the data.
+- Estimating and plotting tools to deliver point forecasts and
+  confidence intervals.
 
 To understand the usage of the `simts` package, please refer to the
 “Vignettes” tab above.
@@ -80,15 +81,27 @@ or [GNU](https://www.gnu.org/licenses/agpl-3.0.en.html) which will
 provide a synopsis of the restrictions placed upon the code.
 
 <!-- ### Requirements and Dependencies -->
+
 <!-- **OS X** -->
+
 <!-- Some users report the need to use X11 to suppress shared library errors. To install X11, visit [xquartz.org](http://www.xquartz.org/). -->
+
 <!-- **Linux** -->
+
 <!-- Both curl and libxml are required. -->
+
 <!-- For **Debian** systems, enter the following in terminal: -->
+
 <!-- ```{r, eval = F, engine='bash'} -->
+
 <!-- sudo apt-get install curl libcurl3 libcurl3-dev libxml2 libxml2-dev -->
+
 <!-- ``` -->
+
 <!-- For **RHEL** systems, enter the following in terminal: -->
+
 <!-- ```{r, eval = F, engine='bash'} -->
+
 <!-- sudo yum install curl curl-devel libxml2 libxml2-dev -->
+
 <!-- ``` -->