zoo {zoo} | R Documentation |
zoo
is the creator for an S3 class of indexed
totally ordered observations which includes irregular
time series.
zoo(x, order.by = index(x), frequency = NULL) ## S3 method for class 'zoo': print(x, style = , quote = FALSE, ...)
x |
a numeric vector, matrix or a factor. |
order.by |
a vector by which the observations in x
are ordered. |
frequency |
numeric indicating frequency of order.by .
If specified, it is checked whether order.by and frequency
comply. If so, a regular "zoo" series is returned, i.e.,
an object of class c("zooreg", "zoo") . See below and
zooreg for more details. |
style |
a string specifying the printing style which can be
"horizontal" (the default for vectors), "vertical"
(the default for matrices) or "plain" (which first prints
first the data and then the index). |
quote |
logical. Should characters be quoted? |
... |
further arguments passed to the print methods of the data and the index. |
zoo
provides infrastructure for ordered observations
which are stored internally in a vector or matrix with an
index attribute (of arbitrary class, see below). The index
must have the same length as NROW(x)
except in the
case of a zero length numeric vector in which case the index
length can be any length. Emphasis has
been given to make all methods independent of the index/time class
(given in order.by
). In principle, the data x
could also
be arbitrary, but currently there is only support for vectors and matrices
and partial support for factors.
zoo
is particularly aimed at irregular time series of numeric
vectors/matrices, but it also supports regular time series (i.e.,
series with a certain frequency
).
zoo
's key design goals are independence of a particular
index/date/time class and consistency
with ts
and base R by providing methods to standard generics. Therefore,
standard functions can be used to work with "zoo"
objects and
memorization of new commands is reduced.
When creating a "zoo"
object with the function zoo
,
the vector of indexes order.by
can be of (a single) arbitrary class
(if x
is shorter or longer than order.by
it is
expanded accordingly),
but it is essential that ORDER(order.by)
works. For other
functions it is assumed that c()
, length()
,
MATCH()
and subsetting [,
work. If this is not the case
for a particular index/date/time class, then methods for these
generic functions should be created by the user. Note, that to achieve this,
new generic functions ORDER
and MATCH
are created in
the zoo
package with default methods corresponding to
the non-generic base functions order
and match
. Furthermore, for certain (but not for all)
operations the index class should have an as.numeric
method (in
particular for regular series) and an as.character
method might improve
printed output (see also below).
If a frequency
is specified when creating a series via zoo
, the
object returned is actually of class "zooreg"
which inherits from "zoo"
.
This is a subclass of "zoo"
which relies on having a "zoo"
series
with an additional "frequency"
attribute (which has to comply with the
index of that series). Regular "zooreg"
series can also be created by
zooreg
, the zoo
analogue of ts
. See the
respective help page and is.regular
for further details.
Methods to standard generics for "zoo"
objects currently
include: print
(see above), summary
, str
, head
,
tail
, [
(subsetting), rbind
, cbind
, merge
(see merge.zoo
), aggregate
(see aggregate.zoo
), barplot
,
plot
and lines
(see plot.zoo
).
To “prettify” printed output of "zoo"
series the generic
function index2char
is used for turning index values into character
values. It defaults to using as.character
but can be customized
if a different printed display should be used (although this should not
be necessary, usually).
The subsetting method [
work essentially like the
corresponding functions for vectors or matrices respectively, i.e., takes
indexes of type "numeric"
, "integer"
or "logical"
. But
additionally, it can be used to index with observations from the index class of
the series. If the index class of the series is one of the three classes above,
the corresponding index has to be encapsulated in I()
to enforce usage of
the index class (see examples).
Additionally, zoo
provides several generic functions and methods
to work (a) on the data contained in a "zoo"
object, (b) the
index (or time) attribute associated to it, and (c) on both data and
index:
(a) The data contained in "zoo"
objects can be extracted by
coredata
(strips off all "zoo"
-specific attributes) and modified
using coredata<-
. Both are new generic functions with methods for
"zoo"
objects, see coredata
.
(b) The index associated with a "zoo"
object can be extracted
by index
and modified by index<-
. As the interpretation
of the index as “time” in time series applications is more natural,
there are also synonymous methods time
and time<-
. The
start and the end of the index/time vector can be queried by
start
and end
. See index
.
(c) To work on both data and index/time, zoo
provides methods
lag
, diff
(see lag.zoo
) and window
,
window<-
(see window.zoo
).
In addition to standard group generic function (see Ops
),
the following mathematical operations are availabe as methods for
"zoo"
objects: transpose t
which coerces to a matrix
first, and cumsum
, cumprod
, cummin
, cummax
which are applied column wise.
Coercion to and from "zoo"
objects is available for objects of
various classes, in particular "ts"
, "irts"
and "its"
objects can be coerced to "zoo"
, the reverse is available for
"its"
and for "irts"
(the latter in package tseries
).
Furthermore, "zoo"
objects can be coerced to vectors, matrices and
lists and data frames (dropping the index/time attribute). See as.zoo
.
Four methods are available for NA
handling in the data of
"zoo"
objects: na.omit
which returns a "zoo"
object with incomplete observations removed, na.locf
which
replaces NA
s by the last previous non-NA
, na.contiguous
which extracts the longest consecutive stretch of non-missing values
in a "zoo"
object and na.approx
which uses
linear interpolation to fill in NA
values.
A typical task to be performed on ordered observations is to evaluate some
function, e.g., computing the mean, in a window of observations that is moved
over the full sample period. The generic function rapply
provides this functionality for arbitrary functions and more efficient versions
rollmean
, rollmax
, rollmedian
are
available for the mean, maximum and median respectively.
A vector or matrix with an "index"
attribute of the same
dimension (NROW(x)
) by which x
is ordered.
zooreg
, plot.zoo
, index
, merge.zoo
## simple creation and plotting x.Date <- as.Date("2003-02-01") + c(1, 3, 7, 9, 14) - 1 x <- zoo(rnorm(5), x.Date) plot(x) time(x) ## subsetting with numeric indexes x[c(2, 4)] ## subsetting with index class x[as.Date("2003-02-01") + c(2, 8)] ## different classes of indexes/times can be used, e.g. numeric vector x <- zoo(rnorm(5), c(1, 3, 7, 9, 14)) ## subsetting with numeric indexes then uses observation numbers x[c(2, 4)] ## subsetting with index class can be enforced by I() x[I(c(3, 9))] ## visualization plot(x) ## or POSIXct y.POSIXct <- ISOdatetime(2003, 02, c(1, 3, 7, 9, 14), 0, 0, 0) y <- zoo(rnorm(5), y.POSIXct) plot(y) ## create a constant series z <- zoo(1, seq(4)[-2]) ## create a 0 dimensional zoo series z0 <- zoo(, 1:4) ## create a 2 dimensional zoo series z2 <- zoo(matrix(1:12, 4, 3), as.Date("2003-01-01") + 0:3) ## create a factor zoo object fz <- zoo(gl(2,5), as.Date("2004-01-01") + 0:9) ## create a zoo series with 0 columns z20 <- zoo(matrix(nrow = 4, ncol = 0), 1:4) ## arithmetic on zoo ojbects intersects them first x1 <- zoo(1:5, 1:5) x2 <- zoo(2:6, 2:6) 10 * x1 + x2 # ifelse does not work with zoo but this works # to create a zoo object which equals x1 at # time i if x1[i] > x1[i-1] and 0 otherwise (diff(x1) > 0) * x1