timeSeries (version 280.75)

as: timeSeries Class, Coercion and Transformation

Description

Functions and methods dealing with the coercion of 'timeSeries' objects. Functions to create 'timeSeries' objects from other objects: ll{ as.timeSeries Generic function to convert an object to a 'timeSeries' object, as.timeSeries.default Returns the unchanged object, as.timeSeries.numeric Converts from a numeric vector, as.timeSseries.data.frame Converts from a numeric vector, as.timeSeries.matrix Converts from a matrix, as.timeSeries.ts Converts from an object of class 'ts', as.timeSeries.character Converts from a named demo file, as.timeSeries.zoo Converts an object of class zoo. } Functions to transform 'timeSeries' objects into other objects: ll{ as.matrix.timeSeries Coerces a 'timeSeries' to a matrix, as.data.frame.timeSeries Coerces a 'timeSeries' to a data.frame, as.ts.timeSeries S3: Coerces a 'timeSeries' to a 'ts' object. as.ts.timeSeries S3: Coerces a 'timeSeries' to a 'logical' object. }

Usage

## S3 method for class 'default':
as.timeSeries(x, \dots) 
## S3 method for class 'data.frame':
as.timeSeries(x, \dots) 
## S3 method for class 'character':
as.timeSeries(x, \dots) 
## S3 method for class 'zoo':
as.timeSeries(x, \dots)## S3 method for class 'timeSeries':
as.matrix(x, \dots)
## S3 method for class 'timeSeries':
as.data.frame(x, row.names = NULL, optional = NULL, \dots)
## S3 method for class 'timeSeries':
as.ts(x, \dots)

Arguments

optional

A logical value. If TRUE, setting row names and converting column names (to syntactic names) is optional.

row.names

NULL or a character vector giving the row names for the data frame. Missing values are not allowed.

x

an object which is coerced according to the generic function.

...

arguments passed to other methods.

Value

• as.timeSeries returns a S4 object of class timeSeries. as.numeric as.data.frame as.matrix as.ts return depending on the generic function a numeric vector, a data frame, a matrix, or an object of class ts.

Examples

## data - timeSeries:
   # Create an artificial timeSeries object:
   setRmetricsOptions(myFinCenter = "GMT")
   charvec = timeCalendar()
   data = matrix(rnorm(12))
   TS = timeSeries(data, charvec, units = "RAND")
   TS

## As Vector:
   as.vector(TS)
   
## As Matrix or Data Frame:
   as.matrix(TS)
   as.data.frame(TS)
   
## As Univariate Object of Class 'ts':
   as.ts(TS)