summary.dbglm {dbstats}R Documentation

Summarizing distance-based generalized linear model fits

Description

summary method for class "dbglm"

Usage

## S3 method for class 'dbglm'
summary(object,dispersion,...)

Arguments

object

an object of class dbglm. Result of dbglm.

dispersion

the dispersion parameter for the family used. Either a single numerical value or NULL (the default)

...

arguments passed to or from other methods to the low level.

Value

A list of class summary.dbglm containing the following components:

call

the matched call.

family

the family object used.

deviance

measure of discrepancy or goodness of fitt. Proportional to twice the difference between the maximum log likelihood achievable and that achieved by the model under investigation.

aic

Akaike's An Information Criterion.

df.residual

the residual degrees of freedom.

null.deviance

the deviance for the null model.

df.null

the residual degrees of freedom for the null model.

iter

number of Fisher Scoring (dblm) iterations.

deviance.resid

the deviance residuals for each observation: sign(y-mu)*sqrt(di).

pears.resid

the raw residual scaled by the estimated standard deviation of y.

dispersion

the dispersion is taken as 1 for the binomial and Poisson families, and otherwise estimated by the residual Chisquared statistic (calculated from cases with non-zero weights) divided by the residual degrees of freedom.

gvar

weighted geometric variability of the squared distance matrix.

gvec

diagonal entries in weighted inner products matrix G.

convcrit

convergence criterion. One of: "DevStat" (stopping criterion 1), "muStat" (stopping criterion 2), "maxiter" (maximum allowed number of iterations has been exceeded).

Author(s)

Boj, Eva <evaboj@ub.edu>, Caballe, Adria <adria.caballe@upc.edu>, Delicado, Pedro <pedro.delicado@upc.edu> and Fortiana, Josep <fortiana@ub.edu>

References

Boj E, Delicado P, Fortiana J (2010). Distance-based local linear regression for functional predictors. Computational Statistics and Data Analysis 54, 429-437.

Boj E, Grane A, Fortiana J, Claramunt MM (2007). Selection of predictors in distance-based regression. Communications in Statistics B - Simulation and Computation 36, 87-98.

Cuadras CM, Arenas C, Fortiana J (1996). Some computational aspects of a distance-based model for prediction. Communications in Statistics B - Simulation and Computation 25, 593-609.

Cuadras C, Arenas C (1990). A distance-based regression model for prediction with mixed data. Communications in Statistics A - Theory and Methods 19, 2261-2279.

Cuadras CM (1989). Distance analysis in discrimination and classification using both continuous and categorical variables. In: Y. Dodge (ed.), Statistical Data Analysis and Inference. Amsterdam, The Netherlands: North-Holland Publishing Co., pp. 459-473.

See Also

dbglm for distance-based generalized linear models.


[Package dbstats version 2.0.2 Index]