Time-series package for R
=========================

Functions in base R:
-------------------

ts		Create a (univariate or multivariate) ts object
[.ts		Subsetting method for ts objects.
as.ts, is.ts	Coercion and membership functions
plot, lines,  print	methods

cbind.ts	cbind method for time series (aligns time bases)
na.omit.ts	na.omit method for time series: omits at ends only
Ops.ts		arithmetic (such as + - * /) for time series

aggregate	Computes summaries (e.g. sum) over disjoint time intervals
diff		Lagged differences of a time series
end		Time of last observation
frequency	Number of observations per unit of time
deltat		Return time interval between observations
time		Create time series giving the times of observations
cycle		Create time series giving the positions in a cycle 
		   of a time series
start		Time of first observation
tsp, tsp<-	Get and set time-series attributes
window		Subset to a time window


Functions in package ts:
-----------------------

acf		Autocovariance and autocorrelation function
acf2AR          Compute an AR Process Exactly Fitting an ACF
ar		Wrapper for autoregression estimation functions
ar.burg		Estimate autoregression model by Burg's method
ar.ols		Estimate autoregression model by ordinary least squares
ar.mle		Estimate autoregression model by maximum likelihood
ar.yw		Estimate autoregression model by solving Yule-Walker equations
arima           ARIMA Modelling of Time Series
arima0		ARIMA modelling -- provisional version
arima.sim       Simulate from an ARIMA Model
ARMAacf         Compute Theoretical ACF for an ARMA Process
ARMAtoMA        Convert ARMA Process to Infinite MA Process
Box.test	Box-Pierce and Ljung-Box tests of independence
ccf		Cross-covariance and cross-correlations for two series
cpgram		Plot cumulative periodogram of univariate time series
decompose	Classical seasonal decomposition by moving averages
diffinv		Discrete integration, the inverse of diff()
embed		Embedding a time series
filter		Linear filtering on a time series
HoltWinters     Holt-Winters Filtering
kernapply	Apply kernel smoothers
kernel		Smoothing kernel objects (and (modified) Daniell, Fejer and 
		   Dirichlet kernels)
lag		Compute lagged version of time series
lag.plot        Time Series Lag Plots
monthplot	Plot a Seasonal or other Subseries
na.contiguous	Find longest contiguous stretch of non-NAs
pacf		Partial autocorrelation function
plot.acf	Plot autocorrelation function
plot.spec	Plot spectral density estimate, coherency and phase.
PP.test		Phillips-Perron test for unit roots
predict		methods for ar, arima, arima0 and StructTS
spec.ar		Estimate spectral density by autoregression
spec.pgram	Estimate spectral density from periodogram
spec.taper	Taper by cosine bell
spectrum	Wrapper for spectral density estimation functions
stl		Seasonal decomposition using loess
stlmethods      Methods for STL Objects
StructTS        Fit Structural Time Series
toeplitz	Generate Toeplitz matrix
ts.intersect	Bind time series as multivariate ts over the common time base
ts.plot		Plot several time series with different time bases
ts.union	Bind time series as multivariate ts over their total time base
tsdiag          Diagnostic Plots for Time-Series Fits
tsSmooth        Use Fixed-Interval Smoothing on Time Series

In some cases the visual output will closer to that of S(-PLUS) if
options(ts.S.compat=TRUE) has been set.


Datasets in base R:
------------------

airmiles	Passenger-Miles on US Airlines 1937-1960
co2		Moana Loa Atmospheric CO2 Concentrations
nhtemp		Yearly Average Temperatures in New Haven CT
presidents	Quarterly Approval Ratings for US Presidents
sunspots	Monthly Mean Relative Sunspot Numbers 1749-1983
uspop		Populations Recorded by the US Census


Datasets in package ts:
----------------------

See data(package="ts").