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 <- 200
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]])
})
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