pDensTime.plot {pdynmc}

Plot Empirical Density of a Column of a Panel Dataset over Time.

Description

pDensTime.plot Plot the empirical density of a column of an object of class 'data.frame' containing a panel dataset across time periods/aggregates of time periods.

Usage

pDensTime.plot(
  object,
  var.name,
  i.name,
  t.name,
  aggregate.t = NULL,
  plot.quantiles = TRUE,
  plot.mean_ci = TRUE,
  plot.extrema = TRUE,
  col.set = c("gray", "navy", "darkorange1", "red"),
  ...
)

Arguments

object

An object of class 'data.frame'.

var.name

Column name of the variable that is plotted (see ‘Details’).

i.name

Column name of cross-section identifier.

t.name

Column name of time-series identifier.

aggregate.t

Argument of data type ‘numeric’. If argument is specified, the corresponding number of time periods is merged (approximately); (defaults to 'NULL').

plot.quantiles

Argument of data type ‘logical’, indicating whether the 5%- and 95%-quantiles and the quartiles should be plotted (as specified by ‘col.set[2]’; defaults to 'TRUE').

plot.mean_ci

Argument of data type ‘logical’, indicating whether the mean and the approximate confidence intervals (mean plus/minus 2 standard deviations) should be plotted (as specified by ‘col.set[3]’; defaults to 'TRUE').

plot.extrema

Argument of data type ‘logical’, indicating whether the minimal and maximal observed value (per time period/group) should be plotted (as specified by ‘col.set[4]’; defaults to 'TRUE').

col.set

Vector of length 4 with entries of data type ‘character’ used to visualize the entities of ‘pDensTime.plot’ (see ‘Details’); must be a valid argument to ‘col2rgb’; defaults to ‘c("gray", "navy", "darkorange1", "red")’.

...

further arguments.

Value

Returns a plot that visualizes the empirical density for a column of a panel dataset contained in an object of class 'data.frame'. The variable of interest is plotted on the ordinate, the longitudinal dimension on the abscissa. For each time period or aggregate of time periods, one empirical density is computed and plotted. Corresponding summary statistics on empirical quantiles and the sample size per longitudinal dimension are included in the plot.

Author(s)

Markus Fritsch, Joachim Schnurbus

See Also

pdynmc for fitting a linear dynamic panel data model.

Examples

## Load data
data(ABdata, package = "pdynmc")
dat <- ABdata
dat[,c(4:7)] <- log(dat[,c(4:7)])

## Minimal set of arguments
pDensTime.plot(object = ABdata, var.name = "emp", i.name = "firm", t.name = "year")

## All arguments explicitly stated
pDensTime.plot(object	= ABdata, var.name	= "emp", i.name	= "firm", t.name	= "year",
 aggregate.t	= NULL,	plot.quantiles	= TRUE, plot.mean_ci	= TRUE, plot.extrema	= TRUE,
 col.set		= c("gray", "navy", "darkorange1", "red"))

## Aggregation over time periods (3 time periods per group)
pDensTime.plot(object = ABdata, var.name = "emp", i.name = "firm", t.name = "year",
 aggregate.t = 3)

## Employ alternative colouring scheme
pDensTime.plot(object = ABdata, var.name = "emp", i.name = "firm", t.name = "year",
 col.set		= c("pink", "blue", "purple", "black"))

## Plot only density, mean, and asymptotic confidence interval
pDensTime.plot(object = ABdata, var.name = "emp", i.name = "firm", t.name = "year",
 plot.quantiles	= FALSE, plot.extrema	= FALSE)