robar: Robust Fit Autoregressive Models to Time Series

In robcor: Robust Correlations

Robust Fit Autoregressive Models to Time Series

Description

Fit an autoregressive time series model to the data using robust algorithms.

Usage

robar(x, order = 2, scaler = "s_FastQn")

Arguments

x	a univariate time series.
order	an order of model to fit.
scaler	location-scale estimator to use in the algorithm. By default, s_FastQn() is used.

Details

This function is a robust replacement for ar().

Note, that implementation and documentation is not finished/polished yet.

Value

A list of class "ar". For description of elements see ar().

Note

WORK-IN-PROGRESS status.

Author(s)

Paul Smirnov <[e-mail]>

References

Shevlyakov, G. L., Lyubomishchenko, N. S. and Smirnov, P. O. (2013). Some remarks on robust estimation of power spectra. Proceedings of the 11th International Conference on Computer Data Analysis and Modeling, Minsk, Belarus, 97–104.

Examples

n <- 100
set.seed(361)
eps <- as.ts(rnorm(n))
x <- arima.sim(list(ar=c(1,-0.9)), n, innov=eps) # basic signal
z <- as.ts(rbinom(n, 1, 0.1) * rnorm(n, sd=10))  # noise
y <- x + z
spec.ar(robar(y, order=2))

robcor documentation built on June 27, 2022, 9:06 a.m.