skellam {VGAM} | R Documentation

## Skellam Distribution Family Function

### Description

Estimates the two parameters of a Skellam distribution by maximum likelihood estimation.

### Usage

    skellam(lmu1 = "loge", lmu2 = "loge", imu1 = NULL, imu2 = NULL,
            nsimEIM = 100, parallel = FALSE, zero = NULL)

### Arguments

`lmu1, lmu2` | Link functions for the mu1 and mu2 parameters. See `Links` for more choices and for general information.
`imu1, imu2` | Optional initial values for the parameters. See `CommonVGAMffArguments` for more information. If convergence failure occurs (this VGAM family function seems to require good initial values) try using these arguments.
`nsimEIM, parallel, zero` | See `CommonVGAMffArguments` for information. In particular, setting `parallel=TRUE` will constrain the two means to be equal.

### Details

The Skellam distribution models the difference between two independent Poisson distributions (with means mu_j, say). It has density function

f(y;mu1,mu2) = ( μ1 / mu_2 )^(y/2) * exp(-mu1-mu2 ) * I_(|y|)( 2 * sqrt(mu1*mu2))

where y is an integer, mu1 > 0, mu2 > 0. Here, I_v is the modified Bessel function of the first kind with order v.

The mean is mu1 - mu2 (returned as the fitted values), and the variance is mu1 + mu2. Simulated Fisher scoring is implemented.

### Value

An object of class `"vglmff"` (see `vglmff-class`). The object is used by modelling functions such as `vglm` and `vgam`.

### Warning

This VGAM family function seems fragile and very sensitive to the initial values. Use very cautiously!!

### Note

Numerical problems may occur for data if mu1 and/or mu2 are large.

### References

Skellam, J. G. (1946) The frequency distribution of the difference between two Poisson variates belonging to different populations. Journal of the Royal Statistical Society, Series A, 109, 296.

### See Also

`dskellam`, `dpois`, `poissonff`.

### Examples

    ## Not run:
    sdata <- data.frame(x2 = runif(nn <- 1000))
    sdata <- transform(sdata, mu1 = exp(1 + x2), mu2 = exp(1 + x2))
    sdata <- transform(sdata, y = rskellam(nn, mu1, mu2))
    fit1 <- vglm(y ~ x2, skellam, data = sdata, trace = TRUE, crit = "coef")
    fit2 <- vglm(y ~ x2, skellam(parallel = TRUE), data = sdata, trace = TRUE)
    coef(fit1, matrix = TRUE)
    coef(fit2, matrix = TRUE)
    summary(fit1)
    # Likelihood ratio test for equal means:
    pchisq(2 * (logLik(fit1) - logLik(fit2)),
           df = df.residual(fit2) - df.residual(fit1), lower.tail = FALSE)
    lrtest(fit1, fit2)  # Alternative

    ## End(Not run)

[Package VGAM version 1.0-3 Index]