| subset.data.list | R Documentation |
Take a subset of a data.list.
## S3 method for class 'data.list' subset( x, subset = NA, nms = NA, kseq = NA, lagforecasts = FALSE, pattern = NA, ... )
x |
The data.list to take a subset of. |
subset |
Given as the integer indexes or a logical vector, or alternatively |
nms |
The names of the variables in |
kseq |
The k horizons of forecasts to be included. |
lagforecasts |
Should the forecasts be lagged k steps (thus useful for plotting etc.). |
pattern |
Regex pattern applied to select the variables in x to be included. |
... |
Not implemented. |
Different arguments can be given to select the subset. See the examples.
a data.list with the subset.
# Use the data.list with building heat load
D <- Dbuilding
# Take a subset for the example
D <- subset(D, 1:10, nms=c("t","Taobs","Ta","Iobs","I"), kseq=1:3)
# Take subset index 2:4
subset(D, 2:4)
# Take subset for a period
subset(D, c("2010-12-15 02:00","2010-12-15 04:00"))
# Cannot request a variable not there
try(subset(D, nms=c("x","Ta")))
# Take specific horizons
subset(D, nms=c("I","Ta"), kseq = 1:2)
subset(D, nms=c("I","Ta"), kseq = 1)
# Lag the forecasts such that they are aligned in time with observations
subset(D, nms=c("Taobs","Ta"), kseq = 2:3, lagforecasts = TRUE)
# The order follows the order in nms
subset(D, nms=c("Ta","I"), kseq = 2)
# Return variables mathing a regex
subset(D, kseq=2, pattern="^I")
# Take data for Ta and lag the forecasts (good for plotting and fitting a model)
X <- subset(Dbuilding, 1:1000, pattern="^Ta", kseq = 10, lagforecasts = TRUE)
# A scatter plot between the forecast and the observations
# (try lagforecasts = FALSE and see the difference)
plot(X$Ta$k10, X$Taobs)
# Fit a model for the 10-step horizon
abline(lm(Taobs ~ Ta.k10, as.data.frame(X)), col=2)