info.poisson.kgroup: Expected Information Matrix for Single or Multiple Group...

In asypow: Calculate Power Utilizing Asymptotic Likelihood Ratio Methods

Description

Calculates expected information matrix for a single observation for single or multiple group Poisson distribution.

The natural null hypothesis for a single group is that that the mean is some specified value. For multiple groups, the natural null hypothesis is that the group means are the same.

Usage

   info.poisson.kgroup(lambda, group.size=1)

Arguments

lambda	Scalar or vector of Poisson means for the groups. The i'th component is the (alternative hypothesis or true) mean of the i'th group.
group.size	Needed only if there are to be several groups with unequal sample sizes. The value of the i'th component is the relative sample size of the i'th group. The calculation made is for a single observation spread over the several groups in proportion to the specified sample size. If this value is specified, it should be a vector of the same length as lambda.

Value

Expected information matrix for a single observation. The matrix is square with dimension equal to the number of groups.

References

Cox, D.R. and Hinkley, D.V. (1974). Theoretical Statistics Chapman and Hall, London.

See Also

info.binomial.kgroup, info.ordinal.kgroup, info.expsurv.kgroup

Examples

# Find the information matrix for a 3 sample Poisson with
# means 1, 2 and 3 and equal sample sizes
info.pois <- info.poisson.kgroup(c(1,2,3))
print(info.pois)

asypow documentation built on May 2, 2019, 2:37 a.m.