R: Moving Functions

moving {fts} | R Documentation

## Moving Functions

### Description

apply summary functions on a moving/rolling basis

### Usage

    moving.mean(x, periods)
    moving.sum(x, periods)
    moving.max(x, periods)
    moving.min(x, periods)
    moving.sd(x, periods)
    moving.rank(x, periods)

    moving.cor(x, y, periods)
    moving.cov(x, y, periods)

    cor.by.row(x,y)

### Arguments

`x` | An Fts object
`y` | An Fts object
`periods` | integer: number of periods in window

### Details

apply a function that takes a vector and returns a scalar on a rolling basis to an fts object.

For cor.by.row, the indicator is not rolling, but is the result of the application of the cor function to matching rows of x and y.

asking for a window larger than the number of rows of the fts object will result in an fts of all NA w/ the same number of rows as the input

for functions that take two fts objects the date intersection is taken before the window function is applied

### Value

an fts object

### Author(s)

Whit Armstrong

### Examples

    x <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=1:100)
    y <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=1:100)

    x.mean <- moving.mean(x,20)
    x.sum <- moving.sum(x,20)
    x.prod <- moving.product(x,20)
    x.max <- moving.max(x,20)
    x.min <- moving.min(x,20)
    x.sd <- moving.sd(x,20)
    x.rank <- moving.rank(x,20)

    ## take only odd rows
    ## to illustrate that teh correlation and covariance
    ## will only be calculated for the intersection of the dates
    y <- y[(1:nrow(y))%%2 == 1]

    xy.cor <- moving.cor(x, y, 20)
    xy.cov <- moving.cov(x, y, 20)

[Package fts version 0.9.9.2 Index]