ARlocpoly: 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

Description

This function uses local polynomial regression to nonparametrically estimate the autoregression function in a nonlinear AR1 model.

Usage

ARlocpoly(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 locpoly.

Value

A list containing

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

Author(s)

L. Han and S. Snyman

References

Fan, J. and Yao, Q. (2008) Nonlinear Time Series: Nonparametric and Parametric Methods. Springer.

Examples

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

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