Burr-Distribution: Burr distribution

Description Usage Arguments Details Value Examples

Description

Density, distribution function, quantile function and random generation for the Burr distribution with a and k two parameters.

Usage

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rburr(n, a, k)

dburr(x, a, k)

pburr(q, a, k)

qburr(p, a, k)

Arguments

n

a number of observations. If length(n) > 1, the length is taken to be the number required.

a

a parameter of the burr distribution

k

a parameter of the burr distribution

x

a vector of quantiles.

q

a vector of quantiles.

p

a vector of probabilities.

Details

The cumulative Burr distribution is

F(x) = 1-( 1 + (x ^ a) ) ^{- k }, x >0, a >0, k > 0

Value

dburr gives the density, pburr gives the distribution function, qburr gives the quantile function, and rburr generates random deviates.

The length of the result is determined by n for rburr, and is the maximum of the lengths of the numerical arguments for the other functions.

The numerical arguments other than n are recycled to the length of the result. Only the first elements of the logical arguments are used.

Examples

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plot(function(x) dburr(x,3,1), 0, 5,ylab="density",
main = " burr density ")

plot(function(x) pburr(x,3,1), 0, 5,ylab="distribution function",
     main = " burr Cumulative ")

plot(function(x) qburr(x,3,1), 0, 1,ylab="quantile",
     main = " burr Quantile ")

#generate a sample of burr distribution of size n
n <- 100
x <- rburr(n, 1, 1)

extremefit documentation built on May 6, 2019, 1:10 a.m.