mwar.ani: Demonstration for "Moving Window Auto-Regression"

In animation: A Gallery of Animations in Statistics and Utilities to Create Animations

Description

This function just fulfills a very naive idea about moving window regression using rectangles to denote the “windows” and move them, and the corresponding AR(1) coefficients as long as rough confidence intervals are computed for data points inside the “windows” during the process of moving.

Usage

mwar.ani(
  x,
  k = 15,
  conf = 2,
  mat = matrix(1:2, 2),
  widths = rep(1, ncol(mat)),
  heights = rep(1, nrow(mat)),
  lty.rect = 2,
  ...
)

Arguments

x	univariate time-series (a single numerical vector); default to be sin(seq(0, 2 * pi, length = 50)) + rnorm(50, sd = 0.2)
k	an integer of the window width
conf	a positive number: the confidence intervals are computed as c(ar1 - conf*s.e., ar1 + conf*s.e.)
mat, widths, heights	arguments passed to layout to divide the device into 2 parts
lty.rect	the line type of the rectangles respresenting the moving “windows”
...	other arguments passed to points in the bottom plot (the centers of the arrows)

Details

The AR(1) coefficients are computed by arima.

Value

A list containing

phi	the AR(1) coefficients
L	lower bound of the confidence interval
U	upper bound of the confidence interval

Author(s)

Yihui Xie

References

Examples at https://yihui.org/animation/example/mwar-ani/

Robert A. Meyer, Jr. Estimating coefficients that change over time. International Economic Review, 13(3):705-710, 1972.

See Also

arima

animation documentation built on Oct. 7, 2021, 9:18 a.m.