sm.ts.pdf: Nonparametric density estimation of stationary time series data
Description
This function estimates the density function of a time series x,
assumed to be stationary. The univariate marginal density is estimated
in all cases; bivariate densities of pairs of lagged values are estimated
depending on the parameter lags.
Usage
sm.ts.pdf(x, h = hnorm(x), lags, maxlag=1, ask=TRUE)
Arguments
x
a vector containing a time series
h
bandwidth
lags
for each value, k say, in the vector lags a density
estimate is produced
of the joint distribution of the pair (x(t-k),x(t)).
maxlag
if lags is not given, it is assigned the value 1:maxlag
(default=1).
ask
if ask=TRUE, the program pauses after each plot, until
is pressed.
...
additional graphical parameters
Value
a list of two elements, containing the outcome of the estimation of
the marginal density and the last bivariate density, as produced by
sm.density.
Side Effects
plots are produced on the current graphical device.
Details
see Section 7.2 of the reference below.
References
Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for
Data Analysis: the Kernel Approach with S-Plus Illustrations.
Oxford University Press, Oxford.