plot.nspmix: Plots a function for an object of class 'nspmix'

In nspmix: Nonparametric and Semiparametric Mixture Estimation

Plots a function for an object of class nspmix

Description

Plots a function for the object of class nspmix, currently either using the plot function of the class or plotting the gradient curve (or its first derivative)

data must belong to a mixture family, as specified by its class.

Class nspmix is an object returned by function cnm, cnmms, cnmpl or cnmap.

Usage

## S3 method for class 'nspmix'
plot(x, data, type = c("probability", "gradient"), ...)

## S3 method for class 'nspmix'
plot(x, data, type=c("probability","gradient"), ...)

Arguments

x	an object of a mixture model class
data	a data set from the mixture model
type	the type of function to be plotted: the probability model of the mixture family (probability), or the gradient function (gradient).
...	arguments passed on to the plot function called.

Details

Function plot.nspmix plots either the mixture model, if the family of the mixture provides an implementation of the generic plot function, or the gradient function.

data must belong to a mixture family, as specified by its class.

Author(s)

Yong Wang <[e-mail]>

References

Wang, Y. (2007). On fast computation of the non-parametric maximum likelihood estimate of a mixing distribution. Journal of the Royal Statistical Society, Ser. B, 69, 185-198.

Wang, Y. (2010). Maximum likelihood computation for fitting semiparametric mixture models. Statistics and Computing, 20, 75-86

Wang, Y. (2007). On fast computation of the non-parametric maximum likelihood estimate of a mixing distribution. Journal of the Royal Statistical Society, Ser. B, 69, 185-198.

Wang, Y. (2010). Maximum likelihood computation for fitting semiparametric mixture models. Statistics and Computing, 20, 75-86

See Also

plot.nspmix, nnls, cnm, cnmms, npnorm, nppois.

nnls, cnm, cnmms, cnmpl, cnmap, npnorm, nppois.

Examples

## Poisson mixture
x = rnppois(200, disc(c(1,4), c(0.7,0.3)))
plot(cnm(x), x)

## Normal mixture
x = rnpnorm(200, disc(c(0,4), c(0.3,0.7)), sd=1)
r = cnm(x, init=list(beta=0.5))   # sd = 0.5
plot(r, x)
plot(r, x, type="g")
plot(r, x, type="g", order=1)


## Poisson mixture
x = rnppois(200, disc(c(1,4), c(0.7,0.3)))
r = cnm(x)
plot(r, x, "p")
plot(r, x, "g")

## Normal mixture
x = rnpnorm(200, mix=disc(c(0,4), c(0.3,0.7)), sd=1)
r = cnm(x, init=list(beta=0.5))   # sd = 0.5
plot(r, x, "p")
plot(r, x, "g")

nspmix documentation built on June 8, 2025, 12:29 p.m.