
Extractor function for the fitted values of a model object that
inherits from a vector linear model (VLM), e.g.,
a model of class "vglm"
.
fittedvlm(object, drop = FALSE, type.fitted = NULL,
percentiles = NULL, ...)
The fitted values evaluated at the final IRLS iteration.
a model object that inherits from a VLM.
Logical.
If FALSE
then the answer is a matrix.
If TRUE
then the answer is a vector.
Character.
Some VGAM family functions have a type.fitted
argument.
If so then a different type of fitted value can be returned.
It is recomputed from the model after convergence.
Note: this is an experimental feature and not all
VGAM family functions have this implemented yet.
See CommonVGAMffArguments
for more details.
See CommonVGAMffArguments
for details.
Currently unused.
Thomas W. Yee
The ``fitted values'' usually corresponds to the mean response, however, because the VGAM package fits so many models, this sometimes refers to quantities such as quantiles. The mean may even not exist, e.g., for a Cauchy distribution.
Note that the fitted value is output from
the @linkinv
slot
of the VGAM family function,
where the eta
argument is
the
Chambers, J. M. and T. J. Hastie (eds) (1992). Statistical Models in S. Wadsworth & Brooks/Cole.
fitted
,
predictvglm
,
vglmff-class
.
# Categorical regression example 1
pneumo <- transform(pneumo, let = log(exposure.time))
(fit1 <- vglm(cbind(normal, mild, severe) ~ let, propodds, pneumo))
fitted(fit1)
# LMS quantile regression example 2
fit2 <- vgam(BMI ~ s(age, df = c(4, 2)),
lms.bcn(zero = 1), data = bmi.nz, trace = TRUE)
head(predict(fit2, type = "response")) # Equals to both these:
head(fitted(fit2))
predict(fit2, type = "response", newdata = head(bmi.nz))
# Zero-inflated example 3
zdata <- data.frame(x2 = runif(nn <- 1000))
zdata <- transform(zdata,
pstr0.3 = logitlink(-0.5 , inverse = TRUE),
lambda.3 = loglink(-0.5 + 2*x2, inverse = TRUE))
zdata <- transform(zdata,
y1 = rzipois(nn, lambda = lambda.3, pstr0 = pstr0.3))
fit3 <- vglm(y1 ~ x2, zipoisson(zero = NULL), zdata, trace = TRUE)
head(fitted(fit3, type.fitted = "mean" )) # E(Y) (the default)
head(fitted(fit3, type.fitted = "pobs0")) # Pr(Y = 0)
head(fitted(fit3, type.fitted = "pstr0")) # Prob of a structural 0
head(fitted(fit3, type.fitted = "onempstr0")) # 1 - Pr(structural 0)
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