cnr: Control Net Reduction

In cpr: Control Polygon Reduction

Control Net Reduction

Description

Run the Control Net Reduction Algorithm.

Usage

cnr(x, margin, n_polycoef = 20L, progress = c("cnr", "influence", "none"), ...)

Arguments

x	a cnr_cn object
margin	the margins to apply the CNR algorithm to. Passed to influence_weights.
n_polycoef	the number of polynomial coefficients to use when assessing the influence of each internal knot.
progress	controls the level of progress messaging.
...	not currently used

Details

cnr runs the control net reduction algorithm.

keep will keep the regression fit as part of the cnr\_cp object for models with up to and including keep fits. For example, if keep = 10 then the resulting cnr\_cnr object will have the regression fit stored in the first keep + 1 (zero internal knots, one internal knot, ..., keep internal knots) cnr\_cp objects in the list. The limit on the number of stored regression fits is to keep memory usage down.

Value

A cpr_cnr object. This is a list of cpr_cn objects.

See Also

cn for defining a control net, influence_weights for finding the influence of the internal knots, cpr for the uni-variable version, Control Polygon Reduction.

vignette(topic = "cnr", package = "cpr")

Examples

acn <- cn(log10(pdg) ~ btensor(list(day, age)
                               , df = list(10, 8)
                               , bknots = list(c(-1, 1), c(44, 53)))
         , data = spdg)
cnr0 <- cnr(acn)
cnr0
summary(cnr0)
plot(cnr0)

cpr documentation built on May 29, 2024, 5:54 a.m.