VGAM (version 1.0-2)

vglm-class: Class ``vglm''

Description

Vector generalized linear models.

Objects from the Class

Objects can be created by calls of the form vglm(...).

Slots

In the following, $M$ is the number of linear predictors.

extra:

Object of class "list"; the extra argument on entry to vglm. This contains any extra information that might be needed by the family function.

family:

Object of class "vglmff". The family function.

iter:

Object of class "numeric". The number of IRLS iterations used.

predictors:

Object of class "matrix" with $M$ columns which holds the $M$ linear predictors.

assign:

Object of class "list", from class "vlm". This named list gives information matching the columns and the (LM) model matrix terms.

call:

Object of class "call", from class "vlm". The matched call.

coefficients:

Object of class "numeric", from class "vlm". A named vector of coefficients.

constraints:

Object of class "list", from class "vlm". A named list of constraint matrices used in the fitting.

contrasts:

Object of class "list", from class "vlm". The contrasts used (if any).

control:

Object of class "list", from class "vlm". A list of parameters for controlling the fitting process. See vglm.control for details.

criterion:

Object of class "list", from class "vlm". List of convergence criterion evaluated at the final IRLS iteration.

df.residual:

Object of class "numeric", from class "vlm". The residual degrees of freedom.

df.total:

Object of class "numeric", from class "vlm". The total degrees of freedom.

dispersion:

Object of class "numeric", from class "vlm". The scaling parameter.

effects:

Object of class "numeric", from class "vlm". The effects.

fitted.values:

Object of class "matrix", from class "vlm". The fitted values.

misc:

Object of class "list", from class "vlm". A named list to hold miscellaneous parameters.

model:

Object of class "data.frame", from class "vlm". The model frame.

na.action:

Object of class "list", from class "vlm". A list holding information about missing values.

offset:

Object of class "matrix", from class "vlm". If non-zero, a $M$-column matrix of offsets.

post:

Object of class "list", from class "vlm" where post-analysis results may be put.

preplot:

Object of class "list", from class "vlm" used by plotvgam; the plotting parameters may be put here.

prior.weights:

Object of class "matrix", from class "vlm" holding the initially supplied weights.

qr:

Object of class "list", from class "vlm". QR decomposition at the final iteration.

R:

Object of class "matrix", from class "vlm". The R matrix in the QR decomposition used in the fitting.

rank:

Object of class "integer", from class "vlm". Numerical rank of the fitted model.

residuals:

Object of class "matrix", from class "vlm". The working residuals at the final IRLS iteration.

ResSS:

Object of class "numeric", from class "vlm". Residual sum of squares at the final IRLS iteration with the adjusted dependent vectors and weight matrices.

smart.prediction:

Object of class "list", from class "vlm". A list of data-dependent parameters (if any) that are used by smart prediction.

terms:

Object of class "list", from class "vlm". The terms object used.

weights:

Object of class "matrix", from class "vlm". The weight matrices at the final IRLS iteration. This is in matrix-band form.

x:

Object of class "matrix", from class "vlm". The model matrix (LM, not VGLM).

xlevels:

Object of class "list", from class "vlm". The levels of the factors, if any, used in fitting.

y:

Object of class "matrix", from class "vlm". The response, in matrix form.

Xm2:

Object of class "matrix", from class "vlm". See vglm-class).

Ym2:

Object of class "matrix", from class "vlm". See vglm-class).

callXm2:

Object of class "call", from class "vlm". The matched call for argument form2.

Extends

Class "vlm", directly.

Methods

cdf

signature(object = "vglm"): cumulative distribution function. Applicable to, e.g., quantile regression and extreme value data models.

deplot

signature(object = "vglm"): Applicable to, e.g., quantile regression.

deviance

signature(object = "vglm"): deviance of the model (where applicable).

plot

signature(x = "vglm"): diagnostic plots.

predict

signature(object = "vglm"): extract the linear predictors or predict the linear predictors at a new data frame.

print

signature(x = "vglm"): short summary of the object.

qtplot

signature(object = "vglm"): quantile plot (only applicable to some models).

resid

signature(object = "vglm"): residuals. There are various types of these.

residuals

signature(object = "vglm"): residuals. Shorthand for resid.

rlplot

signature(object = "vglm"): return level plot. Useful for extreme value data models.

summary

signature(object = "vglm"): a more detailed summary of the object.

References

Yee, T. W. and Hastie, T. J. (2003) Reduced-rank vector generalized linear models. Statistical Modelling, 3, 15--41.

Yee, T. W. and Wild, C. J. (1996) Vector generalized additive models. Journal of the Royal Statistical Society, Series B, Methodological, 58, 481--493.

See Also

vglm, vglmff-class, vgam-class.

Examples

# Multinomial logit model 
pneumo <- transform(pneumo, let = log(exposure.time))
vglm(cbind(normal, mild, severe) ~ let, multinomial, data = pneumo)