hoa (version 2.1.1)

marg.object: Approximate Marginal Inference Object

Description

Class of objects returned when performing approximate conditional inference for regression-scale models.

Arguments

workspace

a list whose elements are the spline interpolations of several first order and higher order statistics. They are used to implement the following likelihood quantities:

- the profile and modified profile/approximate marginal log l

coefficients

a $2\times 2$ matrix containing the unconditional and approximate conditional/marginal MLEs and their standard errors.

call

the function call that created the marg object.

formula

the model formula.

family

the name of the error distribution.

offset

the covariate occurring in the model formula whose coefficient represents the parameter of interest or scale if the parameter of interest is the scale parameter.

diagnostics

diagnostics related to the decomposition of the higher order adjustments into an information and a nuisance parameters term.

n.approx

the number of output points for which the statistics have been calculated exactly.

omitted.val

the range of values omitted in the spline interpolation of some of the higher order statistics considered. The aim is to avoid numerical instabilities around the maximum likelihood estimate.

is.scalar

a logical value indicating whether there are any nuisance parameters. If FALSE there are none.

Generation

This class of objects is returned from calls to the function cond.rsm.

Methods

The class marg has methods for summary, plot, print, coef and family, among others.

References

Barndorff-Nielsen, O. E. (1991) Modified signed log likelihood ratio. Biometrika, 78, 557--564.

Brazzale, A. R. (1999) Approximate conditional inference for logistic and loglinear models. J. Comput. Graph. Statist., 8, 653--661.

Brazzale, A. R. (2000) Practical Small-Sample Parametric Inference. Ph.D. Thesis N. 2230, Department of Mathematics, Swiss Federal Institute of Technology Lausanne.

DiCiccio, T. J., Field, C. A. and Fraser, D. A. S. (1990) Approximations of marginal tail probabilities and inference for scalar parameters. Biometrika, 77, 77--95.

DiCiccio, T. J. and Field, C. A. (1991) An accurate method for approximate conditional and Bayesian inference about linear regression models from censored data. Biometrika, 78, 903--910.

See Also

cond.rsm, summary.marg, plot.marg