Histogram and density plots — HistogramPlot • fBasics

Produce tailored histogram plots and kernel density/log-density estimate plots.

Usage

histPlot(x, labels = TRUE, col = "steelblue", fit = TRUE, 
    title = TRUE, grid = TRUE, rug = TRUE, skip = FALSE, ...) 
densityPlot(x, labels = TRUE, col = "steelblue", fit = TRUE, hist = TRUE, 
    title = TRUE, grid = TRUE, rug = TRUE, skip = FALSE, ...)    
logDensityPlot(x, labels = TRUE, col = "steelblue", robust = TRUE,  
    title = TRUE, grid = TRUE, rug = TRUE, skip = FALSE, ...)

Arguments

x

an object of class "timeSeries".

labels

a logical flag, should the plot be returned with default labels and decorated in an automated way? By default TRUE.

col

the color for the series. In the univariate case use just a color name like the default, col="steelblue", in the multivariate case we recommend to select the colors from a color palette, e.g. col=heat.colors(ncol(x)).

fit

a logical flag, should a fit be added to the plot?

hist

a logical flag, by default TRUE. Should a histogram be laid under the plot?

title

a logical flag, by default TRUE. Should a default title be added to the plot?

grid

a logical flag, should a grid be added to the plot? By default TRUE. To plot a horizontal lines only use grid="h" and for vertical lines use grid="h", respectively.

rug

a logical flag, by default TRUE. Should a rug representation of the data be added to the plot?

skip

a logical flag, should zeros be skipped in the return Series?

robust

a logical flag, by default TRUE. Should a robust fit be added to the plot?

...

optional arguments to be passed on.

Details

histPlot produces a tailored histogram plot.

densityPlot produces a tailored kernel density estimate plot.

logDensityPlot produces a tailored log kernel density estimate plot.

Value

NULL, invisibly. The functions are used for the side effect of producing a plot.

Examples

## data
data(LPP2005REC, package = "timeSeries")
SPI <- LPP2005REC[, "SPI"]
plot(SPI, type = "l", col = "steelblue", main = "SP500")
abline(h = 0, col = "grey")

   
histPlot(SPI) 

   
densityPlot(SPI)