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Density, distribution function, quantile function and random generation for the kappa distribution with shape and scale parameters equal to shape and scale, respectively.
shape
scale
dkappa(x,shape=1,scale=1,log=FALSE) pkappa(q,shape=1,scale=1,lower.tail=TRUE,log.p=FALSE) qkappa(p,shape=1,scale=1,lower.tail=TRUE,log.p=FALSE) rkappa(n,shape=1,scale=1)
vector of quantiles.
vector of probabilities.
number of observations.
shape parameter.
scale parameter.
logical; if TRUE, probabilities p are given as log(p).
logical; if TRUE (default), probabilities are P[X <= x],otherwise, P[X > x].
dkappa gives the density, pkappa gives the distribution function, qkappa gives the quantile function, and rkappa generates random deviates.
dkappa
pkappa
qkappa
rkappa
If X is a random variable distributed according to a kappa distribution, it has density
f(x) = shape/scale*(shape+(x/scale)^shape)^(-(shape+1)/shape)
# NOT RUN { x <- rkappa(1000,12,10) hist(x,freq=FALSE,col='gray',border='white') curve(dkappa(x,12,10),add=TRUE,col='red4',lwd=2) # }
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