Return the altered, inflated and truncated values in a GAIT regression object, else test whether the model is altered, inflated or truncated
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an object of class
any additional arguments, to future-proof this function.
Yee and Ma (2020) propose GAIT regression where values
from three disjoint sets are referred to as special.
These extractor functions return one set each;
they are the
arguments from the family function.
Returns one type of ‘special’ sets associated with GAIT regression.
This is a vector, else a list for truncation.
All three sets are returned by
Some of these functions are subject to change.
Only family functions beginning with
work with these functions, hence
zipoisson fits will return
FALSE or empty
Yee, T. W. and Ma, C. (2020). Generally–altered, –inflated and –truncated regression, with application to heaped and seeped counts. In preparation.
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abdata <- data.frame(y = 0:7, w = c(182, 41, 12, 2, 2, 0, 0, 1)) fit1 <- vglm(y ~ 1, gaitpoisson(alt.mix = 0), data = abdata, weight = w, subset = w > 0) specials(fit1) # All three sets altered(fit1) # Subject to change inflated(fit1) # Subject to change truncated(fit1) # Subject to change is.altered(fit1) is.inflated(fit1) is.truncated(fit1)
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