tsclean: Identify and replace outliers and missing values in a time...

In pli2016/forecast: Forecasting Functions for Time Series and Linear Models

Description

Uses supsmu for non-seasonal series and a periodic stl decompostion with seasonal series to identify outliers. To estimate missing values and outlier replacements, linear interpolation is used on the (possibly seasonally adjusted) series

Usage

tsclean(x, replace.missing = TRUE, lambda = NULL)

Arguments

x	time series
replace.missing	If TRUE, it not only replaces outliers, but also interpolates missing values
lambda	a numeric value giving the Box-Cox transformation parameter

Value

Time series

Author(s)

Rob J Hyndman

See Also

na.interp, tsoutliers, supsmu

Examples

data(gold)
tsclean(gold)

pli2016/forecast documentation built on May 25, 2019, 8:22 a.m.