Davies: The Davies distribution

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Density, distribution function, quantile function and random generation for the Davies distribution

Usage

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 ddavies(x, params)
 pdavies(x, params)
 qdavies(p, params)
 rdavies(n, params)
ddavies.p(x,params)

Arguments

x

quantile

p

vector of probabilities

n

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

params

A three-member vector holding C , lambda1 and~lambda2

Details

The Davies distribution is defined in terms of its quantile function:

Cp^lambda_1/(1-p)^lambda2

It does not have a closed-form probability density function or cumulative density function, so numerical solution is used.

Value

Function ddavies() gives the density, pdavies() gives the distribution function, qdavies() gives the quantile function, and rdavies() generates random deviates.

Author(s)

Robin K. S. Hankin

References

R. K. S. Hankin and A. Lee 2006. “A new family of non-negative distributions” Australia and New Zealand Journal of Statistics, 48(1):67–78

See Also

Gld, fit.davies.p, least.squares, skewness

Examples

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params <- c(10,0.1,0.1)
x <- seq(from=4,to=20,by=0.2)
p <- seq(from=1e-3,to=1-1e-3,len=50)

rdavies(n=5,params)
least.squares(rdavies(100,params))
plot(pdavies(x,params))


plot(p,qdavies(p,params))
plot(x,ddavies(x,params),type="b")

Davies documentation built on May 29, 2017, 3:20 p.m.