ts is used to create time-series objects.
ts(data = NA, start = 1, end = numeric(), frequency = 1, deltat = 1, ts.eps = getOption("ts.eps"), class = , names = ) as.ts(x, ...) is.ts(x)
- a vector or matrix of the observed time-series values. A data frame will be coerced to a numeric matrix via
data.matrix. (See also ‘Details’.)
- the time of the first observation. Either a single number or a vector of two integers, which specify a natural time unit and a (1-based) number of samples into the time unit. See the examples for the use of the second form.
- the time of the last observation, specified in the same way as
- the number of observations per unit of time.
- the fraction of the sampling period between successive observations; e.g., 1/12 for monthly data. Only one of
deltatshould be provided.
- time series comparison tolerance. Frequencies are considered equal if their absolute difference is less than
- class to be given to the result, or none if
"none". The default is
"ts"for a single series,
c("mts", "ts", "matrix")for multiple series.
- a character vector of names for the series in a multiple series: defaults to the colnames of
Series 2, ....
- an arbitrary R object.
- arguments passed to methods (unused for the default method).
ts is used to create time-series objects. These are vector or matrices with class of
"ts" (and additional attributes) which represent data which has been sampled at equispaced points in time. In the matrix case, each column of the matrix
data is assumed to contain a single (univariate) time series. Time series must have at least one observation, and although they need not be numeric there is very limited support for non-numeric series.
"ts" has a number of methods. In particular arithmetic will attempt to align time axes, and subsetting to extract subsets of series can be used (e.g.,
EuStockMarkets[, "DAX"]). However, subsetting the first (or only) dimension will return a matrix or vector, as will matrix subsetting. Subassignment can be used to replace values but not to extend a series (see
window). There is a method for
t that transposes the series as a matrix (a one-column matrix if a vector) and hence returns a result that does not inherit from class
The value of argument
frequency is used when the series is sampled an integral number of times in each unit time interval. For example, one could use a value of
frequency when the data are sampled daily, and the natural time period is a week, or
12 when the data are sampled monthly and the natural time period is a year. Values of
12 are assumed in (e.g.)
is.ts tests if an object is a time series. It is generic: you can write methods to handle specific classes of objects, see InternalMethods.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
print.ts, the print method for time series objects;
plot.ts, the plot method for time series objects. For other definitions of ‘time series’ (e.g., time-ordered observations) see the CRAN task view at http://cran.r-project.org/web/views/TimeSeries.html.
require(graphics) ts(1:10, frequency = 4, start = c(1959, 2)) # 2nd Quarter of 1959 print( ts(1:10, frequency = 7, start = c(12, 2)), calendar = TRUE) # print.ts(.) ## Using July 1954 as start date: gnp <- ts(cumsum(1 + round(rnorm(100), 2)), start = c(1954, 7), frequency = 12) plot(gnp) # using 'plot.ts' for time-series plot ## Multivariate z <- ts(matrix(rnorm(300), 100, 3), start = c(1961, 1), frequency = 12) class(z) head(z) # as "matrix" plot(z) plot(z, plot.type = "single", lty = 1:3) ## A phase plot: plot(nhtemp, c(nhtemp[-1], NA), cex = .8, col = "blue", main = "Lag plot of New Haven temperatures") ## a clearer way to do this would be ## Not run: plot(nhtemp, lag(nhtemp, 1), cex = .8, col = "blue", main = "Lag plot of New Haven temperatures") ## End(Not run)
Documentation reproduced from R 3.0.2. License: GPL-2.