Burr Distribution {extremefit} | R Documentation |
Burr distribution
Description
Density, distribution function, quantile function and random generation for the Burr distribution with a
and k
two parameters.
Usage
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
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)