renamed to cpdetectoR

ontogenerator · Jul 19, 2018 · 23b532b · 23b532b
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,12 +1,12 @@
-Package: cpdetectorr
+Package: cpdetectoR
 Type: Package
 Title: Change point estimation from sequences of choices
 Version: 1.1.0
 Date: 2018-07-17
 Authors@R: person("Vladislav", "Nachev", email = "[email protected]",
   role = c("aut", "cre"))
-URL: http://github.com/ontogenerator/cpdetectorr
-BugReports: http://github.com/ontogenerator/cpdetectorr/issues
+URL: http://github.com/ontogenerator/cpdetectoR
+BugReports: http://github.com/ontogenerator/cpdetectoR/issues
 Description: An R implementation of the learning curve analysis method published
   in Gallistel et al., 2004. From a sequence of responses the changes in response
   (e.g. from one response frequency to another or from one response level to

diff --git a/R/cpdetectorr.R → R/cpdetectoR.R b/R/cpdetectorr.R → R/cpdetectoR.R
@@ -1,11 +1,11 @@
-#' cpdetector: Change point estimation in learning curves
+#' cpdetectoR: Change point estimation in learning curves
 #'
 #' The code is from Gallistel et al. (2004), translated from Matlab to R, with large
 #' portions of comments and original code preserved. The package consists of a few
 #' internal functions and one wrapper function, cp_wrapper.
 #'
 #' @docType package
-#' @name cpdetectorr
+#' @name cpdetectoR
 
 NULL
 

diff --git a/README.Rmd b/README.Rmd
@@ -25,7 +25,7 @@ Based on algorithm published by [Gallistel et al. (2004)](http://dx.doi.org/10.1
 You can use `devtools` to install the package from Github. Install the devtools package first, then execute this code in R(Studio):
 
 ```{r, eval = FALSE}
-devtools::install_github('ontogenerator/cpdetectorr')
+devtools::install_github('ontogenerator/cpdetectoR')
 ```
 
 # Examples
@@ -36,7 +36,7 @@ sequences of responses. The first argument of the function is the input. Thes se
 The input can be either a vector:
 
 ```{r}
-library(cpdetectorr) # load package first
+library(cpdetectoR) # load package first
 set.seed(25)
 cp_wrapper(c(rbinom(50, 1, 0.3), rbinom(50, 1, 0.8)), TRUE, "binomial", 2)
 ```

diff --git a/README.md b/README.md
@@ -9,7 +9,7 @@ Installation
 You can use `devtools` to install the package from Github. Install the devtools package first, then execute this code in R(Studio):
 
 ``` r
-devtools::install_github('ontogenerator/cpdetectorr')
+devtools::install_github('ontogenerator/cpdetectoR')
 ```
 
 Examples
@@ -20,7 +20,7 @@ There is a main wrapper function, called `cp_wrapper`, which can be used to anal
 The input can be either a vector:
 
 ``` r
-library(cpdetectorr) # load package first
+library(cpdetectoR) # load package first
 set.seed(25)
 cp_wrapper(c(rbinom(50, 1, 0.3), rbinom(50, 1, 0.8)), TRUE, "binomial", 2)
 #>   Trial CumSs    Slopes

diff --git a/cpdetectorr.Rproj → cpdetectoR.Rproj b/cpdetectorr.Rproj → cpdetectoR.Rproj
diff --git a/man/cpdetectorr.Rd → man/cpdetectoR.Rd b/man/cpdetectorr.Rd → man/cpdetectoR.Rd
diff --git a/man/eyeblink.Rd b/man/eyeblink.Rd
diff --git a/man/feedingpref.Rd b/man/feedingpref.Rd
diff --git a/man/hopperentry.Rd b/man/hopperentry.Rd
diff --git a/man/matching.Rd b/man/matching.Rd
diff --git a/man/plusmaze.Rd b/man/plusmaze.Rd
diff --git a/man/watermaze.Rd b/man/watermaze.Rd
diff --git a/vignettes/Detecting_change_points.R b/vignettes/Detecting_change_points.R
@@ -5,7 +5,7 @@ knitr::opts_chunk$set(
 )
 
 ## ------------------------------------------------------------------------
-library(cpdetectorr) # load package first
+library(cpdetectoR) # load package first
 set.seed(25)
 cp_wrapper(c(rbinom(50, 1, 0.3), rbinom(50, 1, 0.8)), TRUE, "binomial", 2)
 

diff --git a/vignettes/Detecting_change_points.Rmd b/vignettes/Detecting_change_points.Rmd
@@ -16,7 +16,7 @@ knitr::opts_chunk$set(
 )
 ```
 
-The `cpdetectorr` package is for finding change points in sequences of responses. Putative change
+The `cpdetectoR` package is for finding change points in sequences of responses. Putative change
 points are first detected, then a statistical test at a predefined significance
 level (Criterion) is applied to decide if the change point is supported or not.
 Based on algorithm published by [Gallistel et al. (2004)](http://dx.doi.org/10.1073/pnas.0404965101)^[Gallistel CR, Fairhurst S, Balsam P (2004) The learning curve:
@@ -26,7 +26,7 @@ Based on algorithm published by [Gallistel et al. (2004)](http://dx.doi.org/10.1
 The input can be either a vector:
 
 ```{r}
-library(cpdetectorr) # load package first
+library(cpdetectoR) # load package first
 set.seed(25)
 cp_wrapper(c(rbinom(50, 1, 0.3), rbinom(50, 1, 0.8)), TRUE, "binomial", 2)
 ```

diff --git a/vignettes/Detecting_change_points.html b/vignettes/Detecting_change_points.html
@@ -12,7 +12,7 @@
 
 <meta name="author" content="Vladislav Nachev" />
 
-<meta name="date" content="2018-07-17" />
+<meta name="date" content="2018-07-19" />
 
 <title>Detecting change points</title>
 
@@ -70,13 +70,13 @@
 
 <h1 class="title toc-ignore">Detecting change points</h1>
 <h4 class="author"><em>Vladislav Nachev</em></h4>
-<h4 class="date"><em>2018-07-17</em></h4>
+<h4 class="date"><em>2018-07-19</em></h4>
 
 
 
-<p>The <code>cpdetectorr</code> package is for finding change points in sequences of responses. Putative change points are first detected, then a statistical test at a predefined significance level (Criterion) is applied to decide if the change point is supported or not. Based on algorithm published by <a href="http://dx.doi.org/10.1073/pnas.0404965101">Gallistel et al. (2004)</a><a href="#fn1" class="footnoteRef" id="fnref1"><sup>1</sup></a>, translated from Matlab into R.</p>
+<p>The <code>cpdetectoR</code> package is for finding change points in sequences of responses. Putative change points are first detected, then a statistical test at a predefined significance level (Criterion) is applied to decide if the change point is supported or not. Based on algorithm published by <a href="http://dx.doi.org/10.1073/pnas.0404965101">Gallistel et al. (2004)</a><a href="#fn1" class="footnoteRef" id="fnref1"><sup>1</sup></a>, translated from Matlab into R.</p>
 <p>The input can be either a vector:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(cpdetectorr) <span class="co"># load package first</span>
+<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(cpdetectoR) <span class="co"># load package first</span>
 <span class="kw">set.seed</span>(<span class="dv">25</span>)
 <span class="kw">cp_wrapper</span>(<span class="kw">c</span>(<span class="kw">rbinom</span>(<span class="dv">50</span>, <span class="dv">1</span>, <span class="fl">0.3</span>), <span class="kw">rbinom</span>(<span class="dv">50</span>, <span class="dv">1</span>, <span class="fl">0.8</span>)), <span class="ot">TRUE</span>, <span class="st">&quot;binomial&quot;</span>, <span class="dv">2</span>)
 <span class="co">#&gt;   Trial CumSs    Slopes</span>