R: Estimate Linear Trend using Multitaper Techniques

multitaperTrend {multitaper} | R Documentation

## Estimate Linear Trend using Multitaper Techniques

### Description

Estimate linear trend using inverse spectrum estimation, with the spectrum being computed via multitaper. This technique has improved spectral properties when compared to the least-squares approach. Returned values from this function include the intercept, slope, and centered time array.

### Usage

    multitaperTrend(xd, B, deltat, t.in)

### Arguments

`xd` | Contiguous time series to be detrended.
`B` | Bandwidth to use in estimating trend in physical units; corresponds to NW via equation NW=BT, where N and W are the usual Slepian definitions, and T is the total time elapsed, i.e. T = N*deltat.
`deltat` | Time step for series xd, also used in computing T.
`t.in` | Time array, used in accurately estimating the slope.

### Examples

    x <- 1:101
    y <- 1.0 + 0.5*(x) + rnorm(n=101,mean=0,sd=2)
    vars <- multitaperTrend(xd=y, B=0.05, deltat=1.0, t.in=x)
    plot(x,y,type="l")
    lines(x,vars[[1]]+vars[[2]]*vars[[3]],type="l",col="red")

[Package multitaper version 1.0-13 Index]