binning {sm}R Documentation

Construct frequency table from raw data

Description

Given a vector or a matrix x, this function constructs a frequency table associated to appropriate intervals covering the range of x.

Usage

binning(x, breaks, nbins)

Arguments

x a vector or a matrix with either one or two columns. If x is a one-dimentional matrix, this is equivalent to a vector.
breaks either a vector or a matrix with two columns, assigning the division points of the axis, or the axes in the matrix case. If breaks is not given, it is computed by dividing the range of x into nbins intervals for each of the axes.
nbins the number of intervals on the x axis (in the vector case), or a vector of two elements with the number of intervals on each axes of x (in the marix case). If nbins is not given, a value is computed as round(log(length(x),2)+1) or using a similar expression in the matrix case.

Details

This function is primarity intended for use in connection with sm.density, to estimate noparametrically a density function, when the number of data points is high. To avoid lengthy computations and use of very large matrices, the data are tabulated with the use of binning, and the outcome is passed to sm.density which computes the estimated density curve, using methods described in Chapter 1 of the reference below.

Value

in the vector case, this is a list containing the vector midpoints of the interval midpoints and the frequecies freq associated to them; in the matrix case, the returned value is a list with the following elements: a two-dimensional matrix x with the coordinates of the midpoints of the two-dimensional bins excluding those with 0 frequecies, its associated matrix x.freq of frequencies, the coodinateds of the midpoints, the division points, and the observed frequencies freq.table in full tabular form.

References

Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.

See Also

sm.density, cut,table

Examples

# example of 1-d use
x<-rnorm(1000)
xb<-binning(x)
sm.density(xb$x,h=hnorm(x),weights=xb$freq)
# example of 2-d use
x<-rnorm(1000)
x<-cbind(x,x+rnorm(1000))
xb<-binning(x)
plot(x)
sm.density(xb$x, h=hnorm(x), weights=xb$x.freq, display="slice", add=T)

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