Plots missing values of different types for a time series dataset.
Usage
plot_missing_values(y, show_names = FALSE, show_legend = TRUE,
axis_text_size = NULL, legend_size = NULL, cols = NULL)Arguments
- y
A (\(T\)x\(N\))-matrix of \(N\) time series with \(T\) observations. Data may also be in a time series format (e.g.
ts,zooorxts) or data frame.- show_names
Show the time series' names on the plot (
TRUE) or not (FALSE). Default isTRUE.- show_legend
Logical indicator whether a legend should be displayed. Default is
TRUE.- axis_text_size
Size of the text on the axis. Default takes
ggplot2defaults.- legend_size
Size of the text in the legend if
show_legend = TRUE. Default takesggplot2defaults.- cols
Vector with colours for displaying the different types of data. If the default is overwritten, four colours must be supplied.
Details
The function distinguish four types of data: observed data (non-missing) and three missing types. Type "Balanced NA" indicates where entire rows are missing (NA). These do not cause unbalancedness as the missing rows can simply be deleted. Type "Unbalanced NA" are missing values on the beginning or end of the sample, which cause unbalancedness. These affect some (but not all) bootstrap methods, see e.g.~boot_fdr. Type "Internal NA" are missing values inside the sample, which need to be removed before the bootstrap unit root tests can be used.
This function requires the package ggplot2 to be installed. If the package is not found, plotting is aborted.