R: Forecast Modelling for Online Applications

# Forecast Modelling for Online Applications

## Documentation for package ‘onlineforecast’ version 1.0.2

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

%**% | Multiplication of list with y, elementwise
==.data.list | Determine if two data.lists are identical
AR | Auto-Regressive (AR) input
as.data.frame.data.list | Convert to data.frame
as.data.list | Convert to data.list class
as.data.list.data.frame | Convert to data.list class
aslt | Convertion to POSIXlt
aslt.character | Convertion to POSIXlt
aslt.numeric | Convertion to POSIXlt
aslt.POSIXct | Convertion to POSIXlt
aslt.POSIXlt | Convertion to POSIXlt
bspline | Compute base splines of a variable using the R function 'splines::bs', use in the transform stage.
cache_name | Generation of a name for a cache file for the value of a function.
cache_save | Save a cache file (name generated with 'code_name()'
complete_cases | Find complete cases in forecast matrices
complete_cases.data.frame | Find complete cases in forecast matrices
complete_cases.list | Find complete cases in forecast matrices
ct | Convertion to POSIXct
ct.character | Convertion to POSIXct
ct.numeric | Convertion to POSIXct
ct.POSIXct | Convertion to POSIXct
ct.POSIXlt | Convertion to POSIXct
data.list | Make a data.list
Dbuilding | Observations and weather forecasts from a single-family building, weather station and Danish Meteorological Institute (DMI)
depth | Depth of a list
flattenlist | Flattens list
forecastmodel | Class for forecastmodels
fs | Generation of Fourrier series.
getse | Getting subelement from list.
gof | Simple wrapper for graphics.off()
input_class | Class for forecastmodel inputs
in_range | Selects a period
lagdf | Lagging which returns a data.frame
lagdf.character | Lagging which returns a data.frame
lagdf.data.frame | Lagging which returns a data.frame
lagdf.factor | Lagging which returns a data.frame
lagdf.logical | Lagging which returns a data.frame
lagdf.matrix | Lagging which returns a data.frame
lagdf.numeric | Lagging which returns a data.frame
lagdl | Lagging which returns a data.list
lagvec | Lag by shifting
lapply_cbind | Helper which does lapply and then cbind
lapply_cbind_df | Helper which does lapply, cbind and then as.data.frame
lapply_rbind | Helper which does lapply and then rbind
lapply_rbind_df | Helper which does lapply, rbind and then as.data.frame
lm_fit | Fit an onlineforecast model with 'lm'
lm_optim | Optimize parameters for onlineforecast model fitted with LM
lm_predict | Prediction with an lm forecast model.
long_format | Long format of prediction data.frame
lp | First-order low-pass filtering
lp_vector | First-order low-pass filtering
lp_vector_cpp | Low pass filtering of a vector.
make_input | Make a forecast matrix (as data.frame) from observations.
make_periodic | Make an forecast matrix with a periodic time signal.
make_tday | Make an hour-of-day forecast matrix
nams | Return the column names
nams<- | Return the column names
one | Create ones for model input intercept
pairs.data.list | Generation of pairs plot for a data.list.
par_ts | Set parameters for 'plot_ts()'
pbspline | Wrapper for 'bspline' with 'periodic=TRUE'
persistence | Generate persistence forecasts
plotly_ts | Time series plotting
plotly_ts.data.frame | Time series plotting
plotly_ts.data.list | Time series plotting
plot_ts | Time series plotting
plot_ts.data.frame | Time series plotting
plot_ts.data.list | Time series plotting
plot_ts.matrix | Time series plotting
plot_ts.rls_fit | Time series plotting
plot_ts_iseq | Time series plotting
plot_ts_series | Time series plotting
print.forecastmodel | Print forecast model
print_to_message | Simple function for capturing from the print function and send it in a message().
pst | Simple wrapper for paste0().
resample | Resampling to equidistant time series
resample.data.frame | Resampling to equidistant time series
residuals.data.frame | Calculate the residuals given a forecast matrix and the observations.
residuals.forecastmodel_fit | Calculate the residuals given a forecast matrix and the observations.
residuals.list | Calculate the residuals given a forecast matrix and the observations.
residuals.matrix | Calculate the residuals given a forecast matrix and the observations.
rls_fit | Fit an onlineforecast model with Recursive Least Squares (RLS).
rls_optim | Optimize parameters for onlineforecast model fitted with RLS
rls_predict | Prediction with an rls model.
rls_prm | Function for generating the parameters for RLS regression
rls_summary | Print summary of an onlineforecast model fitted with RLS
rls_update | Updates the model fits
rls_update_cpp | Calculating k-step recursive least squares estimates
rmse | Computes the RMSE score.
score | Calculate the score for each horizon.
score.data.frame | Calculate the score for each horizon.
score.list | Calculate the score for each horizon.
setpar | Setting 'par()' plotting parameters
stairs | Plotting stairs with time point at end of interval.
state_getval | Get the state value kept in last call.
state_setval | Set a state value to be kept for next the transformation function is called.
step_optim | Forward and backward model selection
subset.data.list | Take a subset of a data.list.
summary.data.list | Summary with checks of the data.list for appropriate form.
summary.rls_fit | Print summary of an onlineforecast model fitted with RLS