for CRAN

Author: hoxo-m

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: densratio
 Type: Package
-Version: 0.2.0
+Version: 0.2.1
 Title: Density Ratio Estimation
 Description: Density ratio estimation.
     The estimated density ratio function can be used in many applications such as

R/KLIEP.R

@@ -4,8 +4,8 @@
 #' @param x2 numeric vector or matrix. Data from a denominator distribution q(x).
 #' @param sigma positive numeric vector. Search range of Gaussian kernel bandwidth.
 #' @param kernel_num positive integer. Number of kernels.
-#' @param fold positive integer. Numer of the folds of cross validation.
-#' @param verbose logical(default TRUE).
+#' @param fold positive integer. Number of the folds of cross validation.
+#' @param verbose logical (default TRUE).
 #'
 #' @return KLIEP object that contains a function to compute estimated density ratio.
 #'

R/compute_kernel_Gaussian.R

@@ -15,7 +15,7 @@ kernel_Gaussian <- function(x, y, sigma) {
 #' @param x a numeric vector.
 #' @param y a numeric vector.
 #'
-#' @return squared euclid distance
+#' @return squared Euclid distance
 squared_euclid_distance <- function(x, y) {
   sum((x - y) ^ 2)
 }

README.Rmd

@@ -24,8 +24,8 @@ library(mvtnorm)
 
 <!-- badges: start -->
 [![Travis-CI Build Status](https://travis-ci.org/hoxo-m/densratio.svg?branch=master)](https://travis-ci.org/hoxo-m/densratio)
-[![CRAN Version](http://www.r-pkg.org/badges/version/densratio)](https://CRAN.R-project.org/package=densratio)
-[![CRAN Downloads](http://cranlogs.r-pkg.org/badges/densratio)](http://cranlogs.r-pkg.org/badges/densratio/)
+[![CRAN Version](https://www.r-pkg.org/badges/version/densratio)](https://CRAN.R-project.org/package=densratio)
+[![CRAN Downloads](https://cranlogs.r-pkg.org/badges/densratio)](https://CRAN.R-project.org/package=densratio)
 [![Coverage Status](https://coveralls.io/repos/github/hoxo-m/densratio/badge.svg?branch=master)](https://coveralls.io/github/hoxo-m/densratio?branch=master)
 [![Say Thanks!](https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg)](https://saythanks.io/to/hoxo-m)
 <!-- badges: end -->

README.md

@@ -9,9 +9,9 @@
 [![Travis-CI Build
 Status](https://travis-ci.org/hoxo-m/densratio.svg?branch=master)](https://travis-ci.org/hoxo-m/densratio)
 [![CRAN
-Version](http://www.r-pkg.org/badges/version/densratio)](https://CRAN.R-project.org/package=densratio)
+Version](https://www.r-pkg.org/badges/version/densratio)](https://CRAN.R-project.org/package=densratio)
 [![CRAN
-Downloads](http://cranlogs.r-pkg.org/badges/densratio)](http://cranlogs.r-pkg.org/badges/densratio/)
+Downloads](https://cranlogs.r-pkg.org/badges/densratio)](https://CRAN.R-project.org/package=densratio)
 [![Coverage
 Status](https://coveralls.io/repos/github/hoxo-m/densratio/badge.svg?branch=master)](https://coveralls.io/github/hoxo-m/densratio?branch=master)
 [![Say

man/KLIEP.Rd

@@ -14,6 +14,7 @@ test_that("KLIEP", {
   expected_kernel_weights <- c(0.0885607375, 0.0178664639, 0.0240389107,
                                0.0000000000, 0.0810753470, 0.0001353598)
 
+  testthat::skip_on_cran()
   expect_equal(head(kernel_weights), expected_kernel_weights)
   expect_equal(sigma, 0.09)
 })

man/squared_euclid_distance.Rd

@@ -14,6 +14,7 @@ test_that("RuLSIF", {
   expected_kernel_weights <- c(0.070454411, 0.028303149, 0.003146211,
                                0.010641579, 0.055200243, 0.012069721)
 
+  testthat::skip_on_cran()
   expect_equal(head(kernel_weights), expected_kernel_weights)
   expect_equal(sigma, 0.1)
   expect_equal(lambda, 0.1)

tests/testthat/test-KLIEP.R

@@ -14,6 +14,7 @@ test_that("uLSIF", {
   expected_kernel_weights <- c(0.0674550859, 0.0400446153, 0.0004589047,
                                0.0168489465, 0.0670843163, 0.0189929309)
 
+  testthat::skip_on_cran()
   expect_equal(head(kernel_weights), expected_kernel_weights)
   expect_equal(sigma, 0.1)
   expect_equal(lambda, 1)

tests/testthat/test-RuLSIF.R

@@ -25,7 +25,7 @@ $$
 
 where $x1$ and $x2$ are $d$-dimensional real numbers.
 
-The estimated density ratio function $w(x)$ can be used in many applications such as **anomaly detection** [Hido et al. 2011], **changepoint detection** [Liu et al. 2013], and **covariate shift adaptation** [Sugiyama et al. 2007].
+The estimated density ratio function $w(x)$ can be used in many applications such as **anomaly detection** [Hido et al. 2011], **change-point detection** [Liu et al. 2013], and **covariate shift adaptation** [Sugiyama et al. 2007].
 Other useful applications about density ratio estimation were summarized by [Sugiyama et al. 2012].
 
 The package **densratio** provides a function `densratio()` that returns an object with a method to estimate density ratio as `compute_density_ratio()`.