library(bsts) library(testthat) context("test-regressionholiday.R") set.seed(8675309) trend <- cumsum(rnorm(730, 0, .1)) dates <- seq.Date(from = as.Date("2014-01-01"), length = length(trend), by = "day") y <- zoo(trend + rnorm(length(trend), 0, .2), dates) McmcMatrixReport <- function(draws, truth, confidence = .95) { ## TODO(stevescott): Remove this after Boom 0.8.1 or later is published. Boom ## now includes this function to be used with CheckMcmcMatrix. alpha <- 1 - confidence intervals <- t(apply(draws, 2, quantile, c(alpha / 2, (1 - alpha / 2)))) ans <- cbind(intervals, truth) return(paste(capture.output(print(ans)), collapse = "\n")) } AddHolidayEffect <- function(y, dates, effect) { ## Adds a holiday effect to simulated data. ## Args: ## y: A zoo time series, with Dates for indices. ## dates: The dates of the holidays. ## effect: A vector of holiday effects of odd length. The central effect is ## the main holiday, with a symmetric influence window on either side. ## Returns: ## y, with the holiday effects added. time <- dates - (length(effect) - 1) / 2 for (i in 1:length(effect)) { y[time] <- y[time] + effect[i] time <- time + 1 } return(y) } ## Define some holidays. memorial.day <- NamedHoliday("MemorialDay") #memorial.day.effect <- c(.3, 3, .5) memorial.day.effect <- c(10, 20, 30) memorial.day.dates <- as.Date(c("2014-05-26", "2015-05-25")) y <- AddHolidayEffect(y, memorial.day.dates, memorial.day.effect) presidents.day <- NamedHoliday("PresidentsDay") #presidents.day.effect <- c(.5, 2, .25) presidents.day.effect <- c(40, 50, 60) presidents.day.dates <- as.Date(c("2014-02-17", "2015-02-16")) y <- AddHolidayEffect(y, presidents.day.dates, presidents.day.effect) labor.day <- NamedHoliday("LaborDay") #labor.day.effect <- c(1, 2, 1) labor.day.effect <- c(70, 80, 90) labor.day.dates <- as.Date(c("2014-09-01", "2015-09-07")) y <- AddHolidayEffect(y, labor.day.dates, labor.day.effect) ## The holidays can be in any order. holiday.list <- list(memorial.day, labor.day, presidents.day) number.of.holidays <- length(holiday.list) ## In a real example you'd want more than 100 MCMC iterations. niter <- 500 test_that("regression holiday model works", { ss <- AddLocalLevel(list(), y) ss <- AddRegressionHoliday(ss, y, holiday.list = holiday.list) model <- bsts(y, state.specification = ss, niter = niter, seed = 8675309, ping = niter) expect_that(model, is_a("bsts")) expect_that(model$MemorialDay, is_a("matrix")) expect_that(nrow(model$MemorialDay), equals(niter)) expect_that(ncol(model$MemorialDay), equals(length(memorial.day.effect))) expect_true(CheckMcmcMatrix(model$MemorialDay, memorial.day.effect), info = McmcMatrixReport(model$MemorialDay, memorial.day.effect)) expect_true(CheckMcmcMatrix(model$LaborDay, labor.day.effect), info = McmcMatrixReport(model$LaborDay, labor.day.effect)) expect_true(CheckMcmcMatrix(model$PresidentsDay, presidents.day.effect), info = McmcMatrixReport(model$PresidentsDay, presidents.day.effect)) }) test_that("hierarchical model runs", { ## Try again with some shrinkage. With only 3 holidays there won't be much ## shrinkage. ss2 <- AddLocalLevel(list(), y) ss2 <- AddHierarchicalRegressionHoliday(ss2, y, holiday.list = holiday.list) model2 <- bsts(y, state.specification = ss2, niter = niter, seed = 8675309, ping = niter) expect_that(model2, is_a("bsts")) expect_that(model2$holiday.coefficients, is_a("array")) expect_that(dim(model2$holiday.coefficients), equals(c(niter, number.of.holidays, 3))) } ) test_that("random walk holiday works", { ss <- AddLocalLevel(list(), y) ss <- AddRandomWalkHoliday(ss, y, memorial.day) ss <- AddRandomWalkHoliday(ss, y, labor.day) ss <- AddRandomWalkHoliday(ss, y, presidents.day) model <- bsts(y, state.specification = ss, niter = niter, seed = 8675309, ping = niter) expect_that(model, is_a("bsts")) expect_that(length(dim(model$state.contributions)), equals(3)) expect_true(memorial.day$name %in% dimnames(model$state.contributions)[[2]]) expect_true(labor.day$name %in% dimnames(model$state.contributions)[[2]]) expect_true(presidents.day$name %in% dimnames(model$state.contributions)[[2]]) })