I have the following data structure:
d <- structure(list(Date = structure(c(17349, 17350, 17351, 17352,
17353, 17354, 17355, 17356, 17357, 17358, 17359, 17360, 17361,
17362, 17363, 17364, 17365, 17366, 17367, 17368, 17369, 17370,
17371, 17372, 17373, 17374, 17375, 17376, 17377, 17378, 17379,
17380, 17381, 17382, 17383), class = "Date"), Ratio = c(67, 50,
67, 50, 100, 50, 33, 67, 0, 0, 0, 0, 100, 75, 0, 0, 75, 100,
67, 33, 33, 33, 50, 50, 67, 100, 67, 50, 25, 25, 33, 33, 100,
33, 0)), .Names = c("Date", "Ratio"), row.names = 183:217, class = "data.frame")
And, using the xts package I create a time series like so:
library(xts)
dates = as.Date(d$Date,"%Y-%m-%d")
xs = xts(d$Ratio,dates)
Finally, I attempt to partition the data and train a linear model:
library("forecast")
train.ts <- window(xs, start = as.Date("2017-07-01"), end = as.Date("2017-08-01"))
val.ts <- window(xs, start = as.Date("2017-08-02"), end = as.Date("2017-08-04"))
d.lm <- tslm(train.ts ~ trend + I(trend^2))
Attempting to train the model results in the following error:
Error in forecast:::datamat(train.ts) : replacement has length zero
What is this error and how can I resolve it?
Note: I initially suspected this error was due to NAs throughout the dataset; however, I have since coerced these to zero to no avail!
Edit: This is the full reproducible example (with a suggestion from @Scarabee regarding converting the xts to a ts):
d <- structure(list(Date = structure(c(17349, 17350, 17351, 17352,
17353, 17354, 17355, 17356, 17357, 17358, 17359, 17360, 17361,
17362, 17363, 17364, 17365, 17366, 17367, 17368, 17369, 17370,
17371, 17372, 17373, 17374, 17375, 17376, 17377, 17378, 17379,
17380, 17381, 17382, 17383), class = "Date"), Ratio = c(67, 50,
67, 50, 100, 50, 33, 67, 0, 0, 0, 0, 100, 75, 0, 0, 75, 100,
67, 33, 33, 33, 50, 50, 67, 100, 67, 50, 25, 25, 33, 33, 100,
33, 0)), .Names = c("Date", "Ratio"), row.names = 183:217, class = "data.frame")
library(xts)
dates = as.Date(d$Date,"%Y-%m-%d")
xs = xts(d$Ratio,dates)
library("forecast")
train.ts <- window(xs, start = as.Date("2017-07-01"), end = as.Date("2017-08-01"))
val.ts <- window(xs, start = as.Date("2017-08-02"), end = as.Date("2017-08-04"))
d.lm <- tslm(as.ts(train.ts) ~ trend + I(trend^2)) # results in error Error in [.data.frame(data, , 1) : undefined columns selected
Output of sessionInfo()
:
> sessionInfo()
R version 3.1.0 (2014-04-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forecast_7.1 timeDate_3012.100 xts_0.9-7 zoo_1.7-13
loaded via a namespace (and not attached):
[1] colorspace_1.2-4 fracdiff_1.4-2 ggplot2_2.1.0 grid_3.1.0 gtable_0.1.2 lattice_0.20-29 munsell_0.4.2
[8] nnet_7.3-8 parallel_3.1.0 plyr_1.8.1 quadprog_1.5-5 Rcpp_0.11.1 scales_0.4.0 tools_3.1.0
[15] tseries_0.10-34
Errors updating xts
package:
require(devtools)
# results in error "Error in as.POSIXct.default(value) : do not know how to convert 'value' to class “POSIXct”"
install_version("xts", version = "0.10", repos = "http://cran.us.r-project.org")
# results in error "Warning: invalid package 'https://cran.r-project.org/src/contrib/xts_0.10-0.tar.gz'"
install.packages("https://cran.r-project.org/src/contrib/xts_0.10-0.tar.gz", repos = NULL, type="source")
After updating R and packages forecast
and xts
to their latest versions, the error message is different:
d.lm <- tslm(train.ts ~ trend + I(trend^2))
# Error in names(vars)[length(vars)] <- make.names(colnames(vars[[i]])[j]) :
# replacement has length zero
We can avoid it by converting train.ts
into a ts
object:
d.lm <- tslm(ts(train.ts) ~ trend + I(trend^2))
d.lm
# Call:
# tslm(formula = ts(train.ts) ~ trend + I(trend^2))
#
# Coefficients:
# (Intercept) trend I(trend^2)
# 57.52770 -1.67996 0.04963
Note: it seems that ts()
keeps the index of the times series, while as.ts()
doesn't.
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