| # Licensed to the Apache Software Foundation (ASF) under one or more |
| # contributor license agreements. See the NOTICE file distributed with |
| # this work for additional information regarding copyright ownership. |
| # The ASF licenses this file to You under the Apache License, Version 2.0 |
| # (the "License"); you may not use this file except in compliance with |
| # the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| #------------------------------------------------------------------------------ |
| # R source file to validate LogNormal distribution tests in |
| # org.apache.commons.math.distribution.LogNormalDistributionTest |
| # |
| # To run the test, install R, put this file and testFunctions |
| # into the same directory, launch R from this directory and then enter |
| # source("<name-of-this-file>") |
| # |
| # R functions used |
| # ppareto(q, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE) <-- distribution |
| # The VGAM library which includes the function above must be installed to run |
| # this test. |
| # See https://cran.r-project.org/web/packages/VGAM/index.html |
| #----------------------------------------------------------------------------- |
| tol <- 1E-9 |
| |
| # Function definitions |
| |
| library(VGAM) |
| source("testFunctions") # utility test functions |
| |
| # function to verify distribution computations |
| |
| verifyDistribution <- function(points, expected, mu, sigma, tol) { |
| rDistValues <- rep(0, length(points)) |
| i <- 0 |
| for (point in points) { |
| i <- i + 1 |
| rDistValues[i] <- ppareto(point, mu, sigma) |
| } |
| output <- c("Distribution test mu = ",mu,", sigma = ", sigma) |
| if (assertEquals(expected, rDistValues, tol, "Distribution Values")) { |
| displayPadded(output, SUCCEEDED, WIDTH) |
| } else { |
| displayPadded(output, FAILED, WIDTH) |
| } |
| } |
| |
| # function to verify density computations |
| |
| verifyDensity <- function(points, expected, mu, sigma, tol) { |
| rDensityValues <- rep(0, length(points)) |
| i <- 0 |
| for (point in points) { |
| i <- i + 1 |
| rDensityValues[i] <- dpareto(point, mu, sigma, log = FALSE) |
| } |
| output <- c("Density test mu = ",mu,", sigma = ", sigma) |
| if (assertEquals(expected, rDensityValues, tol, "Density Values")) { |
| displayPadded(output, SUCCEEDED, WIDTH) |
| } else { |
| displayPadded(output, FAILED, WIDTH) |
| } |
| } |
| |
| #-------------------------------------------------------------------------- |
| cat("Pareto test cases\n") |
| |
| mu <- 2.1 |
| sigma <- 1.4 |
| distributionValues <- c(0, 0, 0, 0, 0, 0.791089998892, 0.730456085931, 0.689667290488, 0.645278794701, 0.578763688757) |
| densityValues <- c(0, 0, 0, 0, 0, 0.0455118580441, 0.070444173646, 0.0896924681582, 0.112794186114, 0.151439332084) |
| distributionPoints <- c(-2.226325228634938, -1.156887023657177, -0.643949578356075, -0.2027950777320613, 0.305827808237559, |
| 6.42632522863494, 5.35688702365718, 4.843949578356074, 4.40279507773206, 3.89417219176244) |
| verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol) |
| verifyDensity(distributionPoints, densityValues, mu, sigma, tol) |
| |
| distributionValues <- c(0, 0, 0, 0.510884134236, 0.694625688662, 0.785201995008, 0.837811522357, 0.871634279326) |
| densityValues <- c(0, 0, 0.666666666, 0.195646346305, 0.0872498032394, 0.0477328899983, 0.0294888141169, 0.0197485724114) |
| distributionPoints <- c(mu - 2 *sigma, mu - sigma, mu, mu + sigma, |
| mu + 2 * sigma, mu + 3 * sigma, mu + 4 * sigma, |
| mu + 5 * sigma) |
| verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol) |
| verifyDensity(distributionPoints, densityValues, mu, sigma, tol) |
| |
| mu <- 1 |
| sigma <- 1 |
| distributionPoints <- c(mu - 2 *sigma, mu - sigma, mu, mu + sigma, |
| mu + 2 * sigma, mu + 3 * sigma, mu + 4 * sigma, |
| mu + 5 * sigma) |
| distributionValues <- c(0, 0, 0, 0.5, 0.666666666667, 0.75, 0.8, 0.833333333333) |
| densityValues <- c(0, 0, 1, 0.25, 0.111111111111, 0.0625, 0.04, 0.0277777777778) |
| verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol) |
| verifyDensity(distributionPoints, densityValues, mu, sigma, tol) |
| |
| mu <- 0.1 |
| sigma <- 0.1 |
| distributionPoints <- c(mu - 2 *sigma, 0, mu, mu + sigma, |
| mu + 2 * sigma, mu + 3 * sigma, mu + 4 * sigma, |
| mu + 5 * sigma) |
| distributionValues <- c(0, 0, 0, 0.0669670084632, 0.104041540159, 0.129449436704, 0.148660077479, 0.164041197922) |
| densityValues <- c(0, 0, 1, 0.466516495768, 0.298652819947, 0.217637640824, 0.170267984504, 0.139326467013) |
| verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol) |
| verifyDensity(distributionPoints, densityValues, mu, sigma, tol) |
| |
| displayDashes(WIDTH) |