Weighted.Desc.Stat (version 1.0)

w.hist: weighted histogram

Description

Assume that $x=(x_1, x_2, \cdots , x_n)$ is the observed value of a random sample from a fuzzy population. In classical and usual random sample, the degree of belonging $x_i$ into the random sample is equal to 1, for $1 \leq i \leq n$. But considering fuzzy population, we denote the degree of belonging $x_i$ into the fuzzy population (or into the observed value of random sample) by $\mu_i$ which is a real-valued number from [0,1]. Therefore in such situations, it is more appropriate that we show the observed value of the random sample by notation $ \{ (x_1, \mu_1), (x_2, \mu_2), \cdots , (x_n, \mu_n) \} $ which we called it real-valued fuzzy data. This function drow the weighted histogram for a vector-valued data by considering a vector-valued weight. The weighted histogram containes several classical histograms which are depicted on one two-dimentional sorface. Each classical histogram drown only for the elements of real-value fuzzy data set which their weights are bigger than a cut point belongs to (0,1].

Usage

w.hist(x, mu, breaks, cuts, ylim = NULL, freq = NULL, lwd = NULL)

Arguments

x

A vector-valued numeric data for which the weighted histogram is desired by considering their weights.

mu

A vector of weights of the real-value fuzzy data. The length of this vector must be equal to the length of x and each element of it is belongs to interval [0,1].

breaks

a vector giving the breakpoints between the weighted histogram cells.

cuts

a vector giving the cut-points between (to determine) the classical histograms in the desired weighted histogram.

freq

logical; if TRUE, the histogram graphic is a representation of frequencies, the counts component of the result; if FALSE, probability densities, component density, are plotted (so that the histogram has a total area of one). Defaults to TRUE if and only if breaks are equidistant (and probability is not specified).

ylim

numeric vector of length 2 giving the y limits for the plot. Unused if add = TRUE.

lwd

The line width, a positive number, defaulting to 1. The interpretation is device-specific, and some devices do not implement line widths less than one.

Warning

The length of x and mu must be equal. Also, each element of mu must be in interval [0,1].

Details

The arguments of the weighted histogram can be extended similar to the arguments of usual histogram which is detailed in function "hist" from "graphics" package.

Examples

n = 5000
x = rnorm(n,17,1)
x[x<14 | x>20] = NA
range(x)
mu = runif(n,0,1)
bre = seq(from=14,to=20,len=18)
cu = seq(from=0,to=1,len=10)
w.hist(x, mu, breaks=bre, cuts=cu, ylim=c(0,n/7), lwd = 2)

## The function is currently defined as
function(x, mu, breaks, cuts, ylim = NULL, freq = NULL, lwd = NULL) 
{
Gray = paste("gray", round(seq(from=10, to=100, len=length(cuts)-1)), sep="")
hist(x, col=Gray[1], xlim=range(breaks), ylim=ylim, breaks=breaks, freq=freq, lwd=lwd)
i=2
while(i<=length(cuts))
{
X=x
X[(X*(mu>=cuts[i]))==0]=NA
hist(X, col=Gray[i], xlim=range(breaks), ylim=ylim, breaks=breaks, freq=freq, lwd=lwd, add=TRUE)
i=i+1
}
}