apply: Apply Functions Over Time Series Periods

Description

Apply a function over time series peridos of arbitrary positons and lengths.

Usage

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

an object of class timeSeries.

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

FUN

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

a character value either "monthly" or "quarterly" used in the function applySeries. The default value is "monthly". Only operative when both arguments from and

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 inputs data name is deparsed.

documentation

optional documentation string, or a vector of character strings.

...

arguments passed to other methods.

Details

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 code{fapply} inputs a code{timeSeries} object, and
    if code{from} and code{to} are missing, they take the start 
    and end time stamps of the series as default falues. The function 
    then behaves like code{apply} on the column margin.
    
    Note, the function code{fapply} can be used repetitive in the following
    sense: If code{from} and code{to} are two code{timeDate} vectors of 
    equal length then for each period spanned by the elelemts of the 
    two vectors the function code{FUN} will be applied to each period.
    The resulting time stamps, are the time stamps of the code{to}
    vector. Note, the periods can be regular or irregelar, and they can 
    even overlap. 
    
    The function code{fapply} calls the more general function
    code{applySeries} which also offers, to create automatical monthly
    and quarterly periods.
    
}

examples{
## data - 
   # Percentual Returns of Swiss Bond Index and Performance Index
   LPP = 100 * as.timeSeries(data(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)
   
## Alternative use 
   fapply(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")
}

keyword{chron}