dma.dt: Function wrapper for double moving averages.

In ammarsahab/smoothCV: Wrappers and parameter optimization for time series smoothing methods

Function wrapper for double moving averages.

Description

Function wrapper for double moving averages.

Usage

dma.dt(trainset, m, nahead = 0)

Arguments

trainset	A set of univariate time series data. Can be a vector (type double) or a data.table.
m	Number of most recent observations where the moving average will be taken at each point in time. Should be less than or equal to the length of training set divided by 2.
nahead	Number of observations to predict.

Value

A list containing smoothed (training set, moving averages, level and trend components, and predicted training values) and forc (forecasted values to use against a test set).

Examples

dma.dt(crudenow$close,5,nahead=10)

ammarsahab/smoothCV documentation built on April 18, 2022, 4:39 p.m.