locfit.raw {locfit}R Documentation

Local Regression, Likelihood and Density Estimation.

Usage

locfit.raw(x, y, weights, ...)

Arguments

x Independent variable (or matrix).
y Response variable.
weights Prior weights for observations (reciprocal of variance, or sample size).
cens Censoring indicators for hazard rate or censored regression.
base Baseline parameter estimate.
xlim For density estimation, optional vector of lower and upper bounds for variables.
flim A vector of lower and upper bounds for the evaluation structure. Defaults to the data range.
scale A scale to apply to each variable. Effectively, the data is transformed before fitting, by dividing each component of the independent variable by the corresponding component of scale.
alpha Smoothing parameter. A single number (e.g. alpha=0.7) is interpreted as a nearest neighbor fraction. With two componentes (e.g. alpha=c(0.7,1.2)), the first component is a nearest neighbor fraction, and the second component is a fixed component. A third component is the penalty term in locally adaptive smoothing.
ev Evaluation Structure, default = "tree". Also available are "phull", "data", "grid", "kdtree", "kdcenter", "crossval".
deg Degree of local polynomial. Default: 2 (local quadratic).
family Local likelihood family; "gaussian"; "binomial"; "poisson"; "gamma" and "geom". Density and rate estimation families are "dens", "rate" and "hazard" (hazard rate). A default is selected based on whether or not "y" and "cens" arguments are given; specifying a family argument overrides the default.
link Link function for local likelihood fitting. Depending on the family, choices may be "ident", "log", "logit", "inverse", "sqrt".
maxk Controls space assignment for evaluation structures, default 50
kern Weight function, default = "tcub". Others are "rect", "trwt", "tria", "epan", "bisq" and "gauss". Choices may be restricted when derivatives are required; e.g. for confidence bands and some bandwidth selectors.
kt Kernel type, "sph" (default); "prod". In multivariate problems, Co{"prod"} uses a simplified product model which speeds up computations.
itype Integration type for density estimation.
mint Points for numerical integration rules. Default 20.
maxit Maximum iterations for local likelihood estimation. Default 20.
cut Refinement parameter for adaptive partitions. Default 0.8; smaller values result in more refined partitions.
dc Derivative adjustment.
geth Don't use!
mg Margin size for grids.
deriv Don't use!

Value

An object with class "locfit". A standard set of methods for printing, ploting, etc. these objects is provided.

References

Consult the Web page http://cm.bell-labs.com/stat/project/locfit/.


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