LLW: Local linear weights

In survidm: Inference and Prediction in an Illness-Death Model

Description

Computes local linear weights based on Kernel smoothing.

Usage

LLW(x, kernel = "gaussian", bw, t1)

Arguments

x	Covariate values for obtaining estimates for the conditional probabilities. If missing, unconditioned probabilities will be computed.
kernel	A character string specifying the desired kernel. See details below for possible options. Defaults to "gaussian" where the gaussian density kernel will be used.
bw	A single numeric value to compute a kernel density bandwidth.
t1	Covariate value to compute the weight at.

Details

Possible options for argument window are "gaussian", "epanechnikov", "tricube", "boxcar", "triangular", "quartic" or "cosine".

Value

A vector with local linear weights.

Author(s)

Luis Meira-Machado, Marta Sestelo and Gustavo Soutinho.

See Also

NWW

Examples

LLW(x = colonIDM$age, bw = 3, t1 = 60)

survidm documentation built on June 25, 2021, 1:07 a.m.