period.apply | R Documentation |
Apply a specified function to data over intervals specified by INDEX
. The
intervals are defined as the observations from INDEX[k]+1
to INDEX[k+1]
,
for k = 1:(length(INDEX)-1)
.
period.apply(x, INDEX, FUN, ...)
x |
The data that |
INDEX |
A numeric vector of index breakpoint locations. The vector
should begin with 0 and end with |
FUN |
A function to apply to each interval in |
... |
Additional arguments for |
Similar to the rest of the apply family, period.apply()
calculates the
specified function's value over a subset of data. The primary difference is
that period.apply()
applies the function to non-overlapping intervals of a
vector or matrix.
Useful for applying functions over an entire data object by any
non-overlapping intervals. For example, when INDEX
is the result of a
call to endpoints()
.
period.apply()
checks that INDEX
is sorted, unique, starts with 0, and
ends with nrow(x)
. All those conditions are true of vectors returned by
endpoints()
.
An object with length(INDEX) - 1
observations, assuming INDEX
starts with 0 and ends with nrow(x)
.
When FUN = mean
the results will contain one column for every
column in the input, which is different from other math functions (e.g.
median
, sum
, prod
, sd
, etc.).
FUN = mean
works by column because the default method stats::mean
previously worked by column for matrices and data.frames. R Core changed the
behavior of mean
to always return one column in order to be consistent
with the other math functions. This broke some xts dependencies and
mean.xts()
was created to maintain the original behavior.
Using FUN = mean
will print a message that describes this inconsistency.
To avoid the message and confusion, use FUN = colMeans
to calculate means
by column and use FUN = function(x) mean
to calculate one mean for all the
data. Set options(xts.message.period.apply.mean = FALSE)
to suppress this
message.
Jeffrey A. Ryan, Joshua M. Ulrich
endpoints()
apply.monthly()
zoo.data <- zoo(rnorm(31)+10,as.Date(13514:13744,origin="1970-01-01"))
ep <- endpoints(zoo.data,'weeks')
period.apply(zoo.data, INDEX=ep, FUN=function(x) colMeans(x))
period.apply(zoo.data, INDEX=ep, FUN=colMeans) #same
period.apply(letters,c(0,5,7,26), paste0)
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