apply.monthly: Apply Function over Calendar Periods

In joshuaulrich/xts: eXtensible Time Series

Apply Function over Calendar Periods

Description

Apply a specified function to each distinct period in a given time series object.

Usage

apply.daily(x, FUN, ...)
apply.weekly(x, FUN, ...)
apply.monthly(x, FUN, ...)
apply.quarterly(x, FUN, ...)
apply.yearly(x, FUN, ...)

Arguments

x	an time-series object coercible to xts
FUN	an R function
...	additional arguments to FUN

Details

Simple mechanism to apply a function to non-overlapping time periods, e.g. weekly, monthly, etc. Different from rolling functions in that this will subset the data based on the specified time period (implicit in the call), and return a vector of values for each period in the original data.

Essentially a wrapper to the xts functions endpoints and period.apply, mainly as a convenience.

Value

A vector of results produced by FUN, corresponding to the appropriate periods.

Note

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 used to work 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.

Author(s)

Jeffrey A. Ryan

See Also

endpoints, period.apply, to.monthly

Examples

xts.ts <- xts(rnorm(231),as.Date(13514:13744,origin="1970-01-01"))

start(xts.ts)
end(xts.ts)

apply.monthly(xts.ts,colMeans)
apply.monthly(xts.ts,function(x) var(x))

joshuaulrich/xts documentation built on March 9, 2024, 2:50 a.m.