sharpARlocpoly: Fit a nonlinear AR1 model using local polynomial regression...

In RCMinification: Random Coefficient Minification Time Series Models

Fit a nonlinear AR1 model using local polynomial regression and data sharpening

Description

This function uses local polynomial regression to nonparametrically estimate the autoregression function in a nonlinear AR1 model, after employing data sharpening on the responses.

Usage

sharpARlocpoly(z, deg = 1, h, ...)

Arguments

z	numeric vector of time series observations.
deg	numeric, degree of local polynomial fit.
h	numeric, bandwidth for local polynomial estimate.
...	any other arguments taken by ARlocpoly.

Value

A list containing

x	numeric vector of evaluation points.
y	numeric vector of nonparametric estimates at the values in x.

Author(s)

L. Han and S. Snyman

References

Choi, E., Hall, P. and Rousson, V. (2000) Data Sharpening Methods for Bias Reduction in Nonparametric Regression. Annals of Statistics 28(5):1339-1355.

Examples

x <- nonlinearAR1.sim(100, g = function(x) x*sin(x),  sd = 1.5) # simulated data 
sharpARlocpoly(x, deg = 0, h = 0.5)

RCMinification documentation built on Jan. 17, 2023, 5:14 p.m.