EstTrend: Estimates the trend function for a time series.

In SCEM: Splitting-Coalescence-Estimation Method

Description

The trend function for each individual time series is estimated non-parametrically by the local linear estimate (as discussed in Fan and Gijbels (1996)). Detailed description can be found in Chazin et al. 2019, Supplemental Materials 1.

Usage

EstTrend(y, time, bandwidth)

Arguments

y	A vector of time series observations.
time	A vector of time points where the value of the trend needs to be estimated.
bandwidth	Denotes the order of the bandwidth that should be used in the estimation process. bandwidth = k will mean that the bandwidth is n^k.

Value

A vector of estimated values for the trend function at the given time-points.

Examples

 armenia_split = split(armenia,f = armenia$ID)
 band = -0.33
 z = armenia_split[[1]]$oxygen
 n = length(z)
 ndx = (1:n)/n
 EstTrend(z,ndx,band)

SCEM documentation built on Sept. 5, 2021, 5:50 p.m.