Presents a heatmap with values and a cross table of given Data matrix of two features and a bin width or percentualized values. In this approach the bin width is fixes. A more general way to approach this is the kernel density estimation plot of PDEscatter.
Data: [1:n,1:2] matrix of two features from which the cross table should be generated from
xbins: [1:k] start of k bins as a vector generated with seq of the first feature of data. Default setting assumes percentiled values between zero and 100.
ybins: [1:k] start of k bins as a vector generated with seq of the second feature of data. Normally the same for both features, other settings are only possible if the length k is equal.
NormalizationFactor: Optional, Data feautures can be seen as regular time series, e.g. 1 measurement for a minute, in this case it is useful to normalize the output, e.g. to hours, then NormalizationFactor=60
PlotIt: Optional, Plots the heatmap if TRUE. The first feature is on the x-axis (left to right) and the second on y-axis (bottom to top).
main: In case of for PlotIt=TRUE: title of plot, see title
PlotText: In case of for PlotIt=TRUE: Default TRUE: plots text in heatmap with the values of the crosstable
TextDigits: In case of for TextDigits=TRUE: integer indicating the number of decimal places to use in round.
TextProbs: In case of for TextDigits=TRUE: [1:2] numeric vector of two probabilities defining the thresholds for white text to grey text and grey text to black text, e.g. below the first threshold (Default 0.05) all values (5% of values) will be printed in white because the lowest values of the heatmap are blue. The second value of 0.95 works well if cross table has many zeros; uses quantile internally.
Details
The interval in each bin is closed to the left and opened to the right. The cross table can be seen as a two-dimensional histogram. The idea to add histograms to the table is taken from [Charpentier. 2014].
Returns
The cross table in invisible mode which depicts the number of values (frequency) in an specific range with regard to two features.
The first feature is on the x-axis (left to right), and the second on y-axis (top to bottom) contrary to the plot where it is bottom to top.
References
[Charpentier. 2014] Charpentier, Arthur, ed. Computational actuarial science with R. CRC Press, 2014.
Author(s)
Michael Thrun
Note
For non percentiled values the PlotText part does not seem always to work, but I currently dont know why the text does not always overlap with the heatmap.
See Also
table, image, PDEscatter
Examples
data(ITS)data(MTY)#simple but not a good transformationData=(cbind(ITS/max(ITS),MTY/max(MTY)))*100#choice for bins could be betterCrosstable(Data)