onlineforecast (version 1.0.2)

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

Description

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

Usage

# S3 method for 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)