binning: Data Binning

In bda: Binned Data Analysis

Data Binning

Description

To bin a univariate data set in to a consecutive bins.

Usage

  binning(x, counts, breaks,lower.limit, upper.limit)

Arguments

x	A vector of raw data. 'NA' values will be automatically removed.
counts	Frequencies or counts of observations in different classes (bins)
breaks	The break points for data binning.
lower.limit, upper.limit	The lower and upper limits of the bins.

Details

To create a 'bdata' object. If 'x' is given, a histogram will be created. Otherwise, create a histogram-type data using 'counts' and 'breaks' (or class limits with 'lower.limit' and/or 'upper.limit').

Value

ll	lower limits
ul	upper limits
freq	frequencies
xhist	histogram
xZipf	Zipf plot

Examples

y <- c(10, 21, 56,79,114,122,110,85,85,61,47,49,47,44,31,20,11,4,4)
x <- 14.5 + c(0:length(y))
out1 <- binning(counts=y, breaks=x)
plot(out1)

z = rnorm(100, 34.5, 1.6)
out1 <- binning(z)
plot(out1)

data(FSD)

x <- as.numeric(FirmAge[38,]);
age <- c(0,1:6,11,16,21,26,38);
y <- binning(counts=x, lower.limit=age)
plot(y)
plot(y, type="Zipf")

x <- as.numeric(FirmSize[38,]);
names(FirmSize)
ll <- c(1,5,10,20,50,100,250,500,1000,2500,5000,10000);
ul <- c(4,9,19,49,99,249,499,999,2499,4999,9999,Inf)
y <- binning(counts=x, lower.limit=ll,upper.limit=ul)
plot(y)
plot(y, type="Zipf")

bda documentation built on Sept. 11, 2024, 9:01 p.m.