Title
Usage
xpose.bootgam(
object,
n = n,
id = object@Prefs@Xvardef$id,
oid = "OID",
seed = NULL,
parnam = xvardef("parms", object)[1],
covnams = xvardef("covariates", object),
conv.value = object@Prefs@Bootgam.prefs$conv.value,
check.interval = as.numeric(object@Prefs@Bootgam.prefs$check.interval),
start.check = as.numeric(object@Prefs@Bootgam.prefs$start.check),
algo = object@Prefs@Bootgam.prefs$algo,
start.mod = object@Prefs@Bootgam.prefs$start.mod,
liif = as.numeric(object@Prefs@Bootgam.prefs$liif),
ljif.conv = as.numeric(object@Prefs@Bootgam.prefs$ljif.conv),
excluded.ids = as.numeric(object@Prefs@Bootgam.prefs$excluded.ids),
...
)Arguments
- object
An xpose.data object.
- n
number of bootstrap iterations
- id
column name of id
- oid
create a new column with the original ID data
- seed
random seed
- parnam
ONE (and only one) model parameter name.
- covnams
Covariate names to test on parameter.
- conv.value
Convergence value
- check.interval
How often to check the convergence
- start.check
When to start checking
- algo
Which algorithm to use
- start.mod
which start model
- liif
The liif value
- ljif.conv
The convergence value for the liif
- excluded.ids
ID values to exclude.
- ...
Used to pass arguments to more basic functions.
See also
Other GAM functions:
GAM_summary_and_plot,
xp.get.disp(),
xp.scope3(),
xpose.gam(),
xpose4-package
Examples
if (FALSE) {
## filter out occasion as a covariate as only one value
all_covs <- xvardef("covariates",simpraz.xpdb)
some_covs <- all_covs[!(all_covs %in% "OCC") ]
## here only running n=5 replicates to see that things work
## use something like n=100 for resonable results
boot_gam_obj <- xpose.bootgam(simpraz.xpdb,5,parnam="KA",covnams=some_covs,seed=1234)
}