as: timeSeries Class, Coercion and Transformation

Description

Functions and methods dealing with the coercion of 'timeSeries' objects.

Usage

# S3 method for default
as.timeSeries(x, ...)
# S3 method for ts
as.timeSeries(x, ...) 
# S3 method for data.frame
as.timeSeries(x, ...) 
# S3 method for character
as.timeSeries(x, ...) 
# S3 method for zoo
as.timeSeries(x, ...) 
# S4 method for timeSeries
as.matrix(x, ...)
# S4 method for timeSeries
as.ts(x, ...)
# S4 method for timeSeries
as.data.frame(x, row.names = NULL, optional = FALSE, ...)
# S4 method for timeSeries
as.ts(x, ...)

Value

Function as.timeSeries

returns a S4 object of class 'timeSeries'.

Functions 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.

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.

Details

Functions to create 'timeSeries' objects from other objects:

`as.timeSeries`	Generic to convert an object to a 'timeSeries',
`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:

`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.

Examples

Run this code

## Create an Artificial timeSeries Object - 
   setRmetricsOptions(myFinCenter = "GMT")
   charvec <- timeCalendar()
   data <- matrix(rnorm(12))
   TS <- timeSeries(data, charvec, units = "RAND")
   TS

## Coerce to Vector - 
   as.vector(TS)
   
## Coerce to Matrix - 
   as.matrix(TS)
  
## Coerce to Data Frame - 
   as.data.frame(TS)