sm.ts.pdf {sm} | R Documentation |
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
.
sm.ts.pdf(x, h = hnorm(x), lags, maxlag = 1, ask = TRUE)
x |
a vector containing a time series |
h |
bandwidth |
lags |
for each value, |
maxlag |
if |
ask |
if |
see Section 7.2 of the reference below.
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
.
plots are produced on the current graphical device.
Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.
with(geyser, { sm.ts.pdf(geyser$duration, lags=1:2) })