pairs.data.list: Generation of pairs plot for a data.list.

In onlineforecast: Forecast Modelling for Online Applications

Generation of pairs plot for a data.list.

Description

Generate a pairs plot for the vectors in the data.list.

Usage

## S3 method for class 'data.list'
pairs(
  x,
  subset = NA,
  nms = NA,
  kseq = NA,
  lagforecasts = TRUE,
  pattern = NA,
  lower.panel = NULL,
  panel = panel.smooth,
  pch = 20,
  cex = 0.7,
  ...
)

Arguments

x	The data.list from which to plot.
subset	The subset to be included. Passed to subset.data.list().
nms	The names of the variables to be included. Passed to subset.data.list().
kseq	The horizons to be included. Passed to subset.data.list().
lagforecasts	Lag the forecasts such that they are synced with obervations. Passed to subset.data.list().
pattern	Regex pattern to select the included variables. Passed to subset.data.list().
lower.panel	Passed to pairs().
panel	Passed to pairs().
pch	Passed to pairs().
cex	Passed to pairs().
...	Passed to pairs().

Details

A very useful plot for checking what is in the forecasts, how they are synced and match the observations.

Examples

# Take a subset for the example
D <- subset(Dbuilding, c("2010-12-15","2011-01-15"), pattern="^Ta|^I", kseq=1:3)
pairs(D)

# If the forecasts and the observations are not aligned in time,
# which is easy to see by comparing to the previous plot.
pairs(D, lagforecasts=FALSE)
# Especially for the solar I syncronization is really important!
# Hence if the forecasts were not synced properly, then it can be detected using this type of plot.

# Alternatively, lag when taking the subset
D <- subset(Dbuilding, c("2010-12-15","2011-01-15"), pattern="^Ta|^I", kseq=1:3, lagforecasts=TRUE)
pairs(D, lagforecasts=FALSE)

onlineforecast documentation built on Oct. 12, 2023, 5:15 p.m.