is.buggy {VGAM} | R Documentation |
Checks to see if a fitted object suffers from some known bug.
is.buggy(object, ...) is.buggy.vlm(object, each.term = FALSE, ...)
object |
A fitted VGAM object, e.g., from
|
each.term |
Logical. If |
... |
Unused for now. |
It is known that vgam
with s
terms
do not correctly handle constraint matrices (cmat
, say) when
crossprod(cmat)
is not diagonal.
This function detects whether this is so or not.
Note that probably all VGAM family functions have defaults where all
crossprod(cmat)
s are diagonal, therefore do not suffer from this
bug. It is more likely to occur if the user inputs constraint matrices
using the constraints
argument (and setting zero = NULL
if necessary).
Second-generation VGAMs based on sm.ps
are a
modern alternative to using s
. It does not
suffer from this bug. However, G2-VGAMs require a reasonably
large sample size in order to work more reliably.
The default is a single logical (TRUE
if any term is
TRUE
),
otherwise a vector of such with each element corresponding to a term.
If the value is TRUE
then I suggest replacing the VGAM
by a similar model fitted by vglm
and using
regression splines, e.g., bs
,
ns
.
When the bug is fixed this function may be withdrawn, otherwise
always return FALSE
s!
T. W. Yee
fit1 <- vgam(cbind(agaaus, kniexc) ~ s(altitude, df = c(3, 4)), binomialff(multiple.responses = TRUE), data = hunua) is.buggy(fit1) # Okay is.buggy(fit1, each.term = TRUE) # No terms are buggy fit2 <- vgam(cbind(agaaus, kniexc) ~ s(altitude, df = c(3, 4)), binomialff(multiple.responses = TRUE), data = hunua, constraints = list("(Intercept)" = diag(2), "s(altitude, df = c(3, 4))" = matrix(c(1, 1, 0, 1), 2, 2))) is.buggy(fit2) # TRUE is.buggy(fit2, each.term = TRUE) constraints(fit2) # fit2b is an approximate alternative to fit2: fit2b <- vglm(cbind(agaaus, kniexc) ~ bs(altitude, df = 3) + bs(altitude, df = 4), binomialff(multiple.responses = TRUE), data = hunua, constraints = list("(Intercept)" = diag(2), "bs(altitude, df = 3)" = rbind(1, 1), "bs(altitude, df = 4)" = rbind(0, 1))) is.buggy(fit2b) # Okay is.buggy(fit2b, each.term = TRUE) constraints(fit2b)