version 0.9.3

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: kendallRandomWalks
 Title: Simulate and Visualize Kendall Random Walks and Related
         Distributions
-Version: 0.9.2
+Version: 0.9.3
 Authors@R: person("Mateusz", "Staniak", email = "mateusz.staniak@math.uni.wroc.pl", role = c("aut", "cre"))
 Description: Kendall random walks are a continuous-space Markov chains generated
              by the Kendall generalized convolution. This package provides tools
@@ -11,13 +11,13 @@ Depends: R (>= 3.3)
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
-Imports: ggplot2, dplyr, tidyr, EnvStats, tibble, nleqslv
+Imports: ggplot2, dplyr, tibble, actuar
 RoxygenNote: 6.0.1
 Suggests: knitr, rmarkdown, testthat, covr
 VignetteBuilder: knitr
 NeedsCompilation: no
-Packaged: 2018-06-05 18:33:35 UTC; mtst
+Packaged: 2018-07-10 17:32:39 UTC; mtst
 Author: Mateusz Staniak [aut, cre]
 Maintainer: Mateusz Staniak <mateusz.staniak@math.uni.wroc.pl>
 Repository: CRAN
-Date/Publication: 2018-06-06 11:17:55 UTC
+Date/Publication: 2018-07-10 17:50:03 UTC

MD5

@@ -1,21 +1,21 @@
-802161c45338e0f65405afc5c1e31b88 *DESCRIPTION
+f7f6b43c736ef5b0400aa2373dcde4fd *DESCRIPTION
 127cbfaba59733e6a2c6a1cb068efef0 *LICENSE
 bf40ddb040e1475489436cc818624dbd *NAMESPACE
-d2b472e46a573de5a3285e5a9ddcc53c *NEWS.md
+b82814236c9c10a99ac34f46fc32918f *NEWS.md
 321cb795d29c29dd544278a672d66d3a *R/barrier_crossing.R
 44742a93c96bea8c1e66ebddf3ee3b11 *R/exact_ladder_moments.R
 0c0ea4b64e63a12cf1c77d1e192a3586 *R/kendallRandomPackage.R
-342bab9561ad2b935f5ef3d3363b1951 *R/simulations_kendall_rw.R
+ccb7d17464092e945420bf1a6d0a7685 *R/simulations_kendall_rw.R
 0cdf1ddbbe6db456b3e2761647dbc7cb *R/stable_kendall_distribution.R
 ecc63136d6a466f61e1ed491dad20450 *R/stable_kendall_fit.R
-b6b60ec945f8a1a226a2bcb0d375a493 *README.md
+a418d728965ce0877432a58f9c2c7afe *README.md
 b84cc913d6ce0d3aaec243382c8dfe9d *build/vignette.rds
 a48fdecfe2262ed77d8b61e89c783509 *inst/doc/behaviour.R
 7161eac5f4c752b0251bead321523c98 *inst/doc/behaviour.Rmd
-95472fdbb4e06f604fc52498a3335f38 *inst/doc/behaviour.html
+ad854ec301fd3e50eef4fb93a9d4a793 *inst/doc/behaviour.html
 57b6d03ded5319bbee71626929038290 *inst/doc/kendall_rws.R
 a2ba97d109c7e774099396657baf7dee *inst/doc/kendall_rws.Rmd
-11a135a403e922a11064872a6a20344e *inst/doc/kendall_rws.html
+e51e0c4975e233bfc10da4c19d516d50 *inst/doc/kendall_rws.html
 90cfad0d498cc81140a99dcad617506f *man/Qn.Rd
 bac14a58926029a0fea03be2cf7e4b67 *man/U.Rd
 dce1d5e75d456212d0000537beb067d8 *man/Z.Rd

NEWS.md

@@ -1,8 +1,12 @@
+# kendallRandomPackagae 0.9.3
+
+* `EnvStats` dependency replaced by `actuar`.
+
 # kendallRandomPackage 0.9.2
 
 * Functions for transformations and summaries of simulations of Kendall random walks
   (`summarise_kendall_rw` and `mutate_kendall_rw`).
-
+  
 # kendallRandomPackage 0.9.1
 
 * Numerical computation of G function (so also Williamson transform)

R/simulations_kendall_rw.R

@@ -53,14 +53,14 @@ simulateOneTrajectory <- function(trajectory_length, step_dist,
                                   alpha, symmetric = FALSE, ...) {
   Y <- step_dist(trajectory_length, ...)
   if(symmetric) {
-    theta <- EnvStats::rpareto(trajectory_length,
-                               1,
-                               2*alpha)*sample(c(-1, 1),
+    theta <- actuar::rpareto1(trajectory_length,
+                              2*alpha,
+                              1)*sample(c(-1, 1),
                                                trajectory_length,
                                                prob = c(0.5, 0.5),
                                                replace = TRUE)
   } else {
-    theta <- EnvStats::rpareto(trajectory_length, 1, 2*alpha)
+    theta <- actuar::rpareto1(trajectory_length, 2*alpha, 1)
   }
 
   Xn <- vector("numeric", trajectory_length )

README.md

@@ -1,5 +1,7 @@
-# kendallRandomPackage
+# kendallRandomWalks
 
+[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/kendallRandomWalks)](https://cran.r-project.org/package=kendallRandomWalks)
+[![Total Downloads](http://cranlogs.r-pkg.org/badges/grand-total/kendallRandomWalks?color=orange)](https://cranlogs.r-pkg.org/badges/grand-total/kendallRandomWalks)
 [![Travis-CI Build Status](https://travis-ci.org/mstaniak/kendallRandomPackage.svg?branch=master)](https://travis-ci.org/mstaniak/kendallRandomPackage)
 [![Coverage Status](https://img.shields.io/codecov/c/github/mstaniak/kendallRandomPackage/master.svg)](https://codecov.io/github/mstaniak/kendallRandomPackage?branch=master)
 
@@ -8,26 +10,32 @@
 Simulations and distributions related to Kendall random walks:
 [visit dedicated project page on Researchgate](https://www.researchgate.net/project/First-order-Kendall-maximal-autoregressive-processes-and-their-applications)
 
-Install the newest version:
+To get started, install stable CRAN version
 
->devtools::install_github("mstaniak/kendallRandomPackage")
+> install.packages("kendallRandomWalks")
+
+or the newest version from Github:
+
+> devtools::install_github("mstaniak/kendallRandomPackage")
 
 Help:
->?kendallRandomPackage
+> ?kendallRandomPackage
 
 Main functionalities:
 
   * `simulate_kendall_rw` functions simulates Kendall random walks for a given step distribution. The simulation can be then plotted using generic `plot` function.
   * `transform_kendall_rw` function allows user to play with different scalings and transformations of Kendall random walks to study its properties related to convergence.
+  * `summarise_kendall_rw` and `mutate_kendall_rw` functions allow user to modify or summarise simulated trajectories.
   * `ladder_moment` and `ladder_height` functions help study distribution of first ladder moment and first ladder height empirically.
   * `ladder_moment_pmf` gives exact PMF for first ladder moment.
   * `pkend`, `dkend`, `qkend` and `rkend` are typical functions related to the stable Kendall distribution.
   * `g_function` calculates Williamson transform numerically.
 
-See vignette for examples.
+See vignettes for examples.
 
 If you have a feature request or you found a bug, please leave an issue.
-The goal of this package is to let anyone interested in Kendall convolution/generalized convolutions get familiar with them through visual means and experimentation. 
+
+The goal of this package is to let anyone interested in Kendall convolution/generalized convolutions get familiar with them through visual means and experimentation and aid research in this area by providing tools for simulations. 
 
 
 Acknowledgement