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onlineforecast (version 1.0.1)

Forecast Modelling for Online Applications

Description

A framework for fitting adaptive forecasting models. Provides a way to use forecasts as input to models, e.g. weather forecasts for energy related forecasting. The models can be fitted recursively and can easily be setup for updating parameters when new data arrives. See the included vignettes, the website and the pre-print paper "onlineforecast: An R package for adaptive and recursive forecasting" .

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Version

Install

install.packages('onlineforecast')

Monthly Downloads

337

Version

1.0.1

License

GPL-3

Maintainer

Peder Bacher

Last Published

May 10th, 2022

Functions in onlineforecast (1.0.1)

Find complete cases in forecast matrices

Auto-Regressive (AR) input

Convert to data.list class

Convertion to POSIXlt

Convertion to POSIXct

as.data.frame.data.list

Convert to data.frame

Compute base splines of a variable using the R function splines::bs, use in the transform stage.

Generation of a name for a cache file for the value of a function.

Observations and weather forecasts from a single-family building, weather station and Danish Meteorological Institute (DMI)

Make a data.list

Create ones for model input intercept

Generation of Fourrier series.

Class for forecastmodels

Functions for online forecasting

Lagging which returns a data.list

Wrapper for bspline with periodic=TRUE

Depth of a list

Make a forecast matrix (as data.frame) from observations.

Lag by shifting

Make an forecast matrix with a periodic time signal.

Class for forecastmodel inputs

pairs.data.list

Generation of pairs plot for a data.list.

Generate persistence forecasts

Lagging which returns a data.frame

Set parameters for plot_ts()

summary.data.list

Summary with checks of the data.list for appropriate form.

Optimize parameters for onlineforecast model fitted with RLS

subset.data.list

Take a subset of a data.list.

Fit an onlineforecast model with Recursive Least Squares (RLS).

Save a cache file (name generated with code_name()

Selects a period

Multiplication of list with y, elementwise

Helper which does lapply and then cbind

Determine if two data.lists are identical

Print summary of an onlineforecast model fitted with RLS

Prediction with an lm forecast model.

Long format of prediction data.frame

lapply_cbind_df

Helper which does lapply, cbind and then as.data.frame

Updates the model fits

First-order low-pass filtering

Resampling to equidistant time series

residuals.data.frame

Calculate the residuals given a forecast matrix and the observations.

Low pass filtering of a vector.

Fit an onlineforecast model with lm

Optimize parameters for onlineforecast model fitted with LM

Calculate the score for each horizon.

Getting subelement from list.

Simple wrapper for graphics.off()

print_to_message

Simple function for capturing from the print function and send it in a message().

Setting par() plotting parameters

Plotting stairs with time point at end of interval.

Helper which does lapply and then rbind

Get the state value kept in last call.

Time series plotting

Make an hour-of-day forecast matrix

lapply_rbind_df

Helper which does lapply, rbind and then as.data.frame

Return the column names

Simple wrapper for paste0().

Function for generating the parameters for RLS regression

Prediction with an rls model.

print.forecastmodel

Print forecast model

Calculating k-step recursive least squares estimates

Computes the RMSE score.

Forward and backward model selection

Set a state value to be kept for next the transformation function is called.