timeSeries (version 4030.106)

apply: Apply functions over time series periods

Description

Applies a function to a "timeSeries" object over time periods of arbitrary positons and lengths.

Usage

# S4 method for timeSeries
apply(X, MARGIN, FUN, ..., simplify = TRUE)
fapply(x, from, to, FUN, ...)
applySeries(x, from = NULL, to = NULL, by = c("monthly", "quarterly"), 
            FUN = colMeans, units = NULL, format = x@format, 
            zone = x@FinCenter, FinCenter = x@FinCenter, 
            recordIDs = data.frame(), title = x@title, 
            documentation = x@documentation, ...)

Arguments

x,X

an object of class timeSeries.

MARGIN

a vector giving the subscripts which the function will be applied over, see base R's apply.

FUN

the function to be applied. For the function applySeries the default setting is FUN = colMeans.

simplify

simplify the result?

from, to

starting date and end date as "timeDate" objects. Note, to must be time ordered after from. If from and to are missing in function fapply they are set by default to from=start(x), and to=end(x).

by

a character value either "monthly" or "quarterly" used in the function applySeries. The default value is "monthly". Only operative when both arguments from and to have their default values NULL. In this case the function FUN will be applied to monthly or quarterly periods.

units

an optional character string, which allows to overwrite the current column names of a timeSeries object. By default NULL which means that the column names are selected automatically.

format

the format specification of the input character vector in POSIX notation.

zone

the time zone or financial center where the data were recorded.

FinCenter

a character value with the the location of the financial center named as "continent/city", or "city".

recordIDs

a data frame which can be used for record identification information. Note, this is not yet handled by the apply functions, an empty data.frame will be returned.

title

an optional title string, if not specified the input's data name is deparsed.

documentation

optional documentation string, or a vector of character strings.

...

arguments passed to other methods.

Details

The "timeSeries" method for apply extracts the core data (a matrix) from X and calls apply, passing on all the remaining arguments. If the result is suitable, it converts it to "timeSeries", otherwise returns it as is. ‘Suitable’ here means that it is a matrix or a vector (which is converted to a matrix) and the number of observations is the same as X.

Like apply applies a function to the margins of an array, the function fapply applies a function to the time stamps or signal counts of a financial (therefore the “f” in front of the function name) time series of class "timeSeries".

The function fapply takes a "timeSeries" object as input and if from and to are missing, they are set to the start and end time stamps of the series as default values. The function then behaves like apply on the column margin.

Note, the function fapply can be used repetitively in the following sense: If from and to are two "timeDate" vectors of equal length then for each period spanned by the elements of the two vectors the function FUN will be applied to each period. The resulting time stamps are the time stamps of the to vector. Note, the periods can be regular or irregelar, and they can even overlap.

The function fapply calls the more general function applySeries which also offers, to create automatically monthly and quarterly periods.

Examples

## Percentual Returns of Swiss Bond Index and Performance Index - 
   LPP <- 100 * LPP2005REC[, c("SBI", "SPI")]
   head(LPP, 20)
   
## Aggregate Quarterly Returns -
   applySeries(LPP, by = "quarterly", FUN = colSums)
   
## Aggregate Quarterly every last Friday in Quarter -
   oneDay <- 24*3600
   from <- unique(timeFirstDayInQuarter(time(LPP))) - oneDay
   from <- timeLastNdayInMonth(from, nday = 5)
   to <- unique(timeLastDayInQuarter(time(LPP)))
   to <- timeLastNdayInMonth(to, nday = 5)
   data.frame(from = as.character(from), to = as.character(to))
   applySeries(LPP, from, to, FUN = colSums)
   
## Count Trading Days per Month - 
   colCounts <- function(x) rep(NROW(x), times = NCOL(x))
   applySeries(LPP, FUN = colCounts, by = "monthly")
   
## Alternative Use - 
   fapply(LPP, from, to, FUN = colSums)