makelags_iter: Make lag matrix for iterated prediction

In tanyalrogers/GPEDM: Gaussian Process regression for Empirical Dynamic Modeling

Make lag matrix for iterated prediction

Description

Creates a lag matrix that can be used for making iterated predictions. Runs makelags with specified parameters and forecast=TRUE, then appends nfore-1 empty rows for each pop with timesteps iterated by 1. Requires use of a dataframe and provision of column names.

Usage

makelags_iter(data, nfore, y, pop = NULL, E, tau, time, ...)

Arguments

data	A data frame
nfore	Number of steps to forecast
y	Vector of column names
pop	Column name for pop. Optional.
E	Embedding dimension. Required.
tau	Time delay. Required.
time	Column name for time. Required.
...	Additional arguments passed to makelags

Value

A data frame.

Examples

RHfore2pop=makelags_iter(nfore=50, data=RickerHarvest, 
  y=c("CPUE_index","Catch"), 
  time="Time", tau=1, E=1, pop="Region")

tanyalrogers/GPEDM documentation built on June 1, 2025, 8:10 p.m.