inst/extdata/gentest-1dssa.R

In asl/rssa: A Collection of Methods for Singular Spectrum Analysis

library(testthat)
library(Rssa)
source(system.file("extdata", "common.test.methods.R", package = "Rssa"))

all.svd <- c("svd", "eigen", "propack", "nutrlan")
svd.wo.nutrlan <- c("svd", "eigen", "propack")

co2.td <- make.test.data(series = co2,
                         Ls = c(17, 234, 235, 300, 400),
                         Ls.forecast = c(17, 100, 222, 234),
                         groups = as.list(1:10),
                         groups.forecast = list(1, 1:2, 3:5, 1:5, c(1, 3, 6, 10), 1:10),
                         len = 100,
                         kind = "1d-ssa",
                         svd.method = "e",
                         svd.methods = list(svd.wo.nutrlan, all.svd, all.svd, all.svd, all.svd),
                         svd.methods.forecast = list(svd.wo.nutrlan, all.svd, all.svd, all.svd),
                         tolerance = 2e-7,
                         neig = 20)
test.test.data(test.data = co2.td)


finite.rank.r5ex1 <- function(N) {
  tt <- 1:N
  cos(2*pi*(1:N) / 7) + sin(2*pi*(1:N) / 17) * exp(tt / N * 1.5) + exp(-tt / N * 1.2)
}

fr50 <- finite.rank.r5ex1(50)
fr1k <- finite.rank.r5ex1(1000)
fr50k <- finite.rank.r5ex1(50000)

fr50.td <- make.test.data(series = fr50,
                          Ls = c(17, 25, 40),
                          Ls.forecast = c(17, 24, 25),
                          groups = as.list(1:5),
                          groups.forecast = list(1, 1:2, 3:5, 1:5, 5),
                          len = 100,
                          kind = "1d-ssa",
                          svd.method = "e",
                          svd.methods = list(svd.wo.nutrlan, svd.wo.nutrlan, svd.wo.nutrlan),
                          svd.methods.forecast = list(svd.wo.nutrlan, svd.wo.nutrlan, svd.wo.nutrlan),
                          neig = 5)
test.test.data(test.data = fr50.td)

fr1k.td <- make.test.data(series = fr1k,
                          Ls = c(17, 493, 499, 500, 670),
                          Ls.forecast = c(17, 493, 499, 500),
                          groups = as.list(1:5),
                          groups.forecast = list(1, 1:2, 3:5, 1:5, 5),
                          len = 100,
                          kind = "1d-ssa",
                          svd.method = "e",
                          svd.methods = list(svd.wo.nutrlan, all.svd, all.svd, all.svd, all.svd),
                          svd.methods.forecast = list(svd.wo.nutrlan, all.svd, all.svd, all.svd),
                          neig = 5)
test.test.data(test.data = fr1k.td)

#fr50k.td <- make.test.data(series = fr50k,
#                           Ls = c(17, 493, 23800, 25000, 40000),
#                           Ls.forecast = c(17, 493, 23000, 23800, 25000),
#                           groups = as.list(1:5),
#                           groups.forecast = list(1, 1:2, 3:5, 1:5, 5),
#                           len = 100,
#                           kind = "1d-ssa",
#                           svd.method = "p",
#                           neig = 5,
#                           tolerance = 1e-6,
#                           svd.methods = c("p", "n"))
#test.test.data(test.data = fr50k.td)

set.seed(1)
fr50.nz.td <- make.test.data(series = fr50 + rnorm(fr50),
                             name = "fr50.nz",
                             Ls = c(17, 25, 40),
                             Ls.forecast = c(17, 24, 25),
                             groups = as.list(1:10),
                             groups.forecast = list(1, 1:2, 3:5, 1:5, c(1, 3, 6, 10), 1:10),
                             len = 100,
                             kind = "1d-ssa",
                             svd.method = "e",
                             svd.methods = list(svd.wo.nutrlan, svd.wo.nutrlan, svd.wo.nutrlan),
                             svd.methods.forecast = list(svd.wo.nutrlan, svd.wo.nutrlan, svd.wo.nutrlan),
                             neig = 15)
test.test.data(test.data = fr50.nz.td)

set.seed(1)
fr1k.nz.td <- make.test.data(series = fr1k + rnorm(fr1k),
                             name = "fr1k.nz",
                             Ls = c(17, 493, 499, 500, 670),
                             Ls.forecast = c(17, 493, 499, 500),
                             groups = as.list(1:10),
                             groups.forecast = list(1, 1:2, 3:5, 1:5, c(1, 3, 6, 10), 1:10),
                             len = 100,
                             kind = "1d-ssa",
                             svd.method = "e",
                             svd.methods = list(svd.wo.nutrlan, all.svd, all.svd, all.svd, all.svd),
                             svd.methods.forecast = list(svd.wo.nutrlan, all.svd, all.svd, all.svd),
                             neig = 15)
test.test.data(test.data = fr1k.nz.td)

#set.seed(1)
#fr50k.nz.td <- make.test.data(series = fr50k + rnorm(fr50k),
#                              name = "fr50k.nz",
#                              Ls = c(17, 493, 23800, 25000, 40000),
#                              Ls.forecast = c(17, 493, 23000, 23800, 25000),
#                              groups = as.list(1:10),
#                              groups.forecast = list(1, 1:2, 3:5, 1:5, c(1, 3, 6, 10), 1:10),
#                              len = 100,
#                              kind = "1d-ssa",
#                              svd.method = "p",
#                              neig = 15,
#                              tolerance = 1e-6,
#                              svd.methods = c("p", "n"))
#test.test.data(test.data = fr50k.nz.td)

#save(co2.td, fr50.td, fr1k.td, fr50k.td, fr50.nz.td, fr1k.nz.td, fr50k.nz.td,
save(co2.td, fr50.td, fr1k.td, fr50.nz.td, fr1k.nz.td,
     file = system.file("extdata", "1dssa.testdata.rda", package = "Rssa"),
     compress = "xz", compression_level = 9)