Merge pull request #20 from permaverse/remove-lmjl-alea

Remove all occurences to LMJL-Alea GitHub organization in favour of n…

NEWS.md

@@ -62,7 +62,7 @@ R-release due to pandoc version not available preventing the `pvalue-function` v
 test is performed.
 * Add a function to compute p-value functions for sets of null hypotheses.
 * Draft of article illustrating the computation of p-value functions with
-[**flipr**](https://lmjl-alea.github.io/flipr/).
+[**flipr**](https://permaverse.github.io/flipr/).
 * Add $t$, mean and Fisher test statistics.
 * Correct two-tail p-value computation.
 * Better API for pvalue function.

README.Rmd

@@ -13,49 +13,52 @@ knitr::opts_chunk$set(
 )
 ```
 
-# Overview <a href='https://lmjl-alea.github.io/flipr/'><img src='man/figures/logo.png' align="right" height="139" /></a>
+# Overview <a href='https://permaverse.github.io/flipr/'><img src='man/figures/logo.png' align="right" height="139" /></a>
 
 <!-- badges: start -->
-[![R-CMD-check](https://github.com/LMJL-Alea/flipr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/LMJL-Alea/flipr/actions/workflows/R-CMD-check.yaml)
-[![test-coverage](https://github.com/LMJL-Alea/flipr/workflows/test-coverage/badge.svg)](https://github.com/LMJL-Alea/flipr/actions)
-[![Codecov test coverage](https://codecov.io/gh/LMJL-Alea/flipr/branch/master/graph/badge.svg)](https://codecov.io/gh/LMJL-Alea/flipr?branch=master)
-[![pkgdown](https://github.com/LMJL-Alea/flipr/workflows/pkgdown/badge.svg)](https://github.com/LMJL-Alea/flipr/actions)
+[![R-CMD-check](https://github.com/permaverse/flipr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/permaverse/flipr/actions/workflows/R-CMD-check.yaml)
+[![test-coverage](https://github.com/permaverse/flipr/workflows/test-coverage/badge.svg)](https://github.com/permaverse/flipr/actions)
+[![Codecov test coverage](https://codecov.io/gh/permaverse/flipr/branch/master/graph/badge.svg)](https://codecov.io/gh/permaverse/flipr?branch=master)
+[![pkgdown](https://github.com/permaverse/flipr/workflows/pkgdown/badge.svg)](https://github.com/permaverse/flipr/actions)
 [![CRAN status](https://www.r-pkg.org/badges/version/flipr)](https://CRAN.R-project.org/package=flipr)
 <!-- badges: end -->
 
-The goal of the [**flipr**](https://lmjl-alea.github.io/flipr/) package is to
+The goal of the [**flipr**](https://permaverse.github.io/flipr/) package is to
 provide a flexible framework for making inference via permutation. The idea is
 to promote the permutation framework as an incredibly well-suited tool for
 inference on complex data. You supply your data, as complex as it might be, in
 the form of lists in which each entry stores one data point in a representation
-that suits you and [**flipr**](https://lmjl-alea.github.io/flipr/) takes care of
+that suits you and [**flipr**](https://permaverse.github.io/flipr/) takes care of
 the permutation magic and provides you with either point estimates or confidence
 regions or $p$-value of hypothesis tests. Permutation tests are especially
 appealing because they are exact no matter how small or big your sample sizes
 are. You can also use the so-called *non-parametric combination* approach in
 this setting to combine several statistics to better target the alternative
 hypothesis you are testing against. Asymptotic consistency is also guaranteed
 under mild conditions on the statistic you use. The
-[**flipr**](https://lmjl-alea.github.io/flipr/) package provides a flexible
+[**flipr**](https://permaverse.github.io/flipr/) package provides a flexible
 permutation framework for making inference such as point estimation, confidence
 intervals or hypothesis testing, on any kind of data, be it univariate,
 multivariate, or more complex such as network-valued data, topological data,
 functional data or density-valued data.
 
 ## Installation
 
-You can install the latest stable version of
-[**flipr**](https://lmjl-alea.github.io/flipr/) on CRAN with:
+You can install the package from [CRAN](https://CRAN.R-project.org) with:
+
 ``` r
 install.packages("flipr")
 ```
 
-Or you can install the development version from [GitHub](https://github.com/) with:
+Alternatively, You can install the development version of
+[**flipr**](https://permaverse.github.io/flipr/) from
+[GitHub](https://github.com/) with:
 
 ``` r
-# install.packages("remotes")
-remotes::install_github("LMJL-Alea/flipr")
+# install.packages("pak")
+pak::pak("permaverse/flipr")
 ```
+
 ## Example
 
 ```{r}
@@ -64,7 +67,7 @@ library(flipr)
 
 We hereby use the very simple t-test for comparing the means of two univariate
 samples to show how easy it is to carry out a permutation test with
-[**flipr**](https://lmjl-alea.github.io/flipr/).
+[**flipr**](https://permaverse.github.io/flipr/).
 
 ### Data generation
 
@@ -98,12 +101,12 @@ null_spec <- function(y, parameters) {
 
 Next, we need to decide which test statistic(s) we are going to use for performing the test. Here, we are only interested in one parameter, namely the mean difference $\delta$. Since the two samples share the same variance, we can use for example the $t$-statistic with a pooled estimate of the common variance.
 
-This statistic can be easily computed using `stats::t.test(x, y, var.equal = TRUE)$statistic`. However, we want to extend its evaluation to any permuted version of the data. Test statistic functions compatible with [**flipr**](https://lmjl-alea.github.io/flipr/) should have at least two mandatory input arguments:
+This statistic can be easily computed using `stats::t.test(x, y, var.equal = TRUE)$statistic`. However, we want to extend its evaluation to any permuted version of the data. Test statistic functions compatible with [**flipr**](https://permaverse.github.io/flipr/) should have at least two mandatory input arguments:
 
 - `data` which is either a concatenated list of size $n_x + n_y$ regrouping the data points of both samples or a distance matrix of size $(n_x + n_y) \times (n_x + n_y)$ stored as an object of class `dist`.
 - `indices1` which is an integer vector of size $n_x$ storing the indices of the data points belonging to the first sample in the current permuted version of the data.
 
-Some test statistics are already implemented in [**flipr**](https://lmjl-alea.github.io/flipr/) and ready to use. User-defined test statistics can be used as well, with the use of the helper function `use_stat(nsamples = 2, stat_name = )`. This function creates and saves an `.R` file in the `R/` folder of the current working directory and populates it with the following template:
+Some test statistics are already implemented in [**flipr**](https://permaverse.github.io/flipr/) and ready to use. User-defined test statistics can be used as well, with the use of the helper function `use_stat(nsamples = 2, stat_name = )`. This function creates and saves an `.R` file in the `R/` folder of the current working directory and populates it with the following template:
 ```{r, eval=FALSE}
 #' Test Statistic for the Two-Sample Problem
 #'
@@ -141,7 +144,7 @@ stat_{{{name}}} <- function(data, indices1) {
 }
 ```
 
-For instance, a [**flipr**](https://lmjl-alea.github.io/flipr/)-compatible version of the $t$-statistic with pooled variance will look like:
+For instance, a [**flipr**](https://permaverse.github.io/flipr/)-compatible version of the $t$-statistic with pooled variance will look like:
 ```{r}
 my_t_stat <- function(data, indices1) {
   n <- if (inherits(data, "dist"))
@@ -172,7 +175,7 @@ stat_functions <- list(my_t_stat)
 
 ### Assign test statistics to parameters
 
-Finally we need to define a named list that tells [**flipr**](https://lmjl-alea.github.io/flipr/) which test statistics among the ones declared in the `stat_functions` list should be used for each parameter under investigation. This is used to determine bounds on each parameter for the plausibility function. This list, often termed `stat_assignments`, should therefore have as many elements as there are parameters under investigation. Each element should be named after a parameter under investigation and should list the indices corresponding to the test statistics that should be used for that parameter in `stat_functions`. In our example, it boils down to:
+Finally we need to define a named list that tells [**flipr**](https://permaverse.github.io/flipr/) which test statistics among the ones declared in the `stat_functions` list should be used for each parameter under investigation. This is used to determine bounds on each parameter for the plausibility function. This list, often termed `stat_assignments`, should therefore have as many elements as there are parameters under investigation. Each element should be named after a parameter under investigation and should list the indices corresponding to the test statistics that should be used for that parameter in `stat_functions`. In our example, it boils down to:
 ```{r}
 stat_assignments <- list(delta = 1)
 ```

README.md

@@ -1,26 +1,26 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# Overview <a href='https://lmjl-alea.github.io/flipr/'><img src='man/figures/logo.png' align="right" height="139" /></a>
+# Overview <a href='https://permaverse.github.io/flipr/'><img src='man/figures/logo.png' align="right" height="139" /></a>
 
 <!-- badges: start -->
 
-[![R-CMD-check](https://github.com/LMJL-Alea/flipr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/LMJL-Alea/flipr/actions/workflows/R-CMD-check.yaml)
-[![test-coverage](https://github.com/LMJL-Alea/flipr/workflows/test-coverage/badge.svg)](https://github.com/LMJL-Alea/flipr/actions)
+[![R-CMD-check](https://github.com/permaverse/flipr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/permaverse/flipr/actions/workflows/R-CMD-check.yaml)
+[![test-coverage](https://github.com/permaverse/flipr/workflows/test-coverage/badge.svg)](https://github.com/permaverse/flipr/actions)
 [![Codecov test
-coverage](https://codecov.io/gh/LMJL-Alea/flipr/branch/master/graph/badge.svg)](https://codecov.io/gh/LMJL-Alea/flipr?branch=master)
-[![pkgdown](https://github.com/LMJL-Alea/flipr/workflows/pkgdown/badge.svg)](https://github.com/LMJL-Alea/flipr/actions)
+coverage](https://codecov.io/gh/permaverse/flipr/branch/master/graph/badge.svg)](https://codecov.io/gh/permaverse/flipr?branch=master)
+[![pkgdown](https://github.com/permaverse/flipr/workflows/pkgdown/badge.svg)](https://github.com/permaverse/flipr/actions)
 [![CRAN
 status](https://www.r-pkg.org/badges/version/flipr)](https://CRAN.R-project.org/package=flipr)
 <!-- badges: end -->
 
-The goal of the [**flipr**](https://lmjl-alea.github.io/flipr/) package
+The goal of the [**flipr**](https://permaverse.github.io/flipr/) package
 is to provide a flexible framework for making inference via permutation.
 The idea is to promote the permutation framework as an incredibly
 well-suited tool for inference on complex data. You supply your data, as
 complex as it might be, in the form of lists in which each entry stores
 one data point in a representation that suits you and
-[**flipr**](https://lmjl-alea.github.io/flipr/) takes care of the
+[**flipr**](https://permaverse.github.io/flipr/) takes care of the
 permutation magic and provides you with either point estimates or
 confidence regions or $p$-value of hypothesis tests. Permutation tests
 are especially appealing because they are exact no matter how small or
@@ -29,7 +29,7 @@ big your sample sizes are. You can also use the so-called
 statistics to better target the alternative hypothesis you are testing
 against. Asymptotic consistency is also guaranteed under mild conditions
 on the statistic you use. The
-[**flipr**](https://lmjl-alea.github.io/flipr/) package provides a
+[**flipr**](https://permaverse.github.io/flipr/) package provides a
 flexible permutation framework for making inference such as point
 estimation, confidence intervals or hypothesis testing, on any kind of
 data, be it univariate, multivariate, or more complex such as
@@ -38,19 +38,20 @@ data.
 
 ## Installation
 
-You can install the latest stable version of
-[**flipr**](https://lmjl-alea.github.io/flipr/) on CRAN with:
+You can install the package from [CRAN](https://CRAN.R-project.org)
+with:
 
 ``` r
 install.packages("flipr")
 ```
 
-Or you can install the development version from
+Alternatively, You can install the development version of
+[**flipr**](https://permaverse.github.io/flipr/) from
 [GitHub](https://github.com/) with:
 
 ``` r
-# install.packages("remotes")
-remotes::install_github("LMJL-Alea/flipr")
+# install.packages("pak")
+pak::pak("permaverse/flipr")
 ```
 
 ## Example
@@ -61,7 +62,7 @@ library(flipr)
 
 We hereby use the very simple t-test for comparing the means of two
 univariate samples to show how easy it is to carry out a permutation
-test with [**flipr**](https://lmjl-alea.github.io/flipr/).
+test with [**flipr**](https://permaverse.github.io/flipr/).
 
 ### Data generation
 
@@ -119,8 +120,8 @@ This statistic can be easily computed using
 `stats::t.test(x, y, var.equal = TRUE)$statistic`. However, we want to
 extend its evaluation to any permuted version of the data. Test
 statistic functions compatible with
-[**flipr**](https://lmjl-alea.github.io/flipr/) should have at least two
-mandatory input arguments:
+[**flipr**](https://permaverse.github.io/flipr/) should have at least
+two mandatory input arguments:
 
 - `data` which is either a concatenated list of size $n_x + n_y$
   regrouping the data points of both samples or a distance matrix of
@@ -131,7 +132,7 @@ mandatory input arguments:
   current permuted version of the data.
 
 Some test statistics are already implemented in
-[**flipr**](https://lmjl-alea.github.io/flipr/) and ready to use.
+[**flipr**](https://permaverse.github.io/flipr/) and ready to use.
 User-defined test statistics can be used as well, with the use of the
 helper function `use_stat(nsamples = 2, stat_name = )`. This function
 creates and saves an `.R` file in the `R/` folder of the current working
@@ -175,7 +176,7 @@ stat_{{{name}}} <- function(data, indices1) {
 ```
 
 For instance, a
-[**flipr**](https://lmjl-alea.github.io/flipr/)-compatible version of
+[**flipr**](https://permaverse.github.io/flipr/)-compatible version of
 the $t$-statistic with pooled variance will look like:
 
 ``` r
@@ -214,7 +215,7 @@ stat_functions <- list(my_t_stat)
 ### Assign test statistics to parameters
 
 Finally we need to define a named list that tells
-[**flipr**](https://lmjl-alea.github.io/flipr/) which test statistics
+[**flipr**](https://permaverse.github.io/flipr/) which test statistics
 among the ones declared in the `stat_functions` list should be used for
 each parameter under investigation. This is used to determine bounds on
 each parameter for the plausibility function. This list, often termed