Man pages for onlineforecast
Forecast Modelling for Online Applications

ARAuto-Regressive (AR) input
as.data.frame.data.listConvert to data.frame
as.data.listConvert to data.list class
asltConvertion to POSIXlt
bsCompute base splines of a variable using the R function...
cache_nameGeneration of a name for a cache file for the value of a...
cache_saveSave a cache file (name generated with 'code_name()'
complete_casesFind complete cases in forecast matrices
ctConvertion to POSIXct
data.listMake a data.list
DbuildingObservations and weather forecasts from a single-family...
depthDepth of a list
equals-.data.listDetermine if two data.lists are identical
flattenlistFlattens list
forecastmodelClass for forecastmodels
fsGeneration of Fourrier series.
getseGetting subelement from list.
gofSimple wrapper for graphics.off()
grapes-times-times-grapesMultiplication of list with y, elementwise
input_classClass for forecastmodel inputs
in_rangeSelects a period
lagdfLagging which returns a data.frame
lagdf.characterLagging which returns a data.frame
lagdf.factorLagging which returns a data.frame
lagdf.logicalLagging which returns a data.frame
lagdf.matrixLagging which returns a data.frame
lagdf.numericLagging which returns a data.frame
lagdlLagging which returns a data.list
lagvecLag by shifting
lapply_cbindHelper which does lapply and then cbind
lapply_cbind_dfHelper which does lapply, cbind and then as.data.frame
lapply_rbindHelper which does lapply and then rbind
lapply_rbind_dfHelper which does lapply, rbind and then as.data.frame
lm_fitFit an onlineforecast model with 'lm'
lm_optimOptimize parameters for onlineforecast model fitted with LM
lm_predictPrediction with an lm forecast model.
long_formatLong format of prediction data.frame
lpFirst-order low-pass filtering
lp_vectorFirst-order low-pass filtering
lp_vector_cppLow pass filtering of a vector.
make_inputMake a forecast matrix (as data.frame) from observations.
make_periodicMake an forecast matrix with a periodic time signal.
make_tdayMake an hour-of-day forecast matrix
namsReturn the column names
oneCreate ones for model input intercept
onlineforecast-packageonlineforecast: Forecast Modelling for Online Applications
pairs.data.listGeneration of pairs plot for a data.list.
par_tsSet parameters for 'plot_ts()'
pbsplineWrapper for 'bspline' with 'periodic=TRUE'
persistenceGenerate persistence forecasts
plotly_ts.data.frameTime series plotting
plotly_ts.data.listTime series plotting
plot_tsTime series plotting
print.forecastmodelPrint forecast model
print_to_messageSimple function for capturing from the print function and...
pstSimple wrapper for paste0().
resampleResampling to equidistant time series
resample.data.frameResampling to equidistant time series
residualsCalculate the residuals given a forecast matrix and the...
rls_fitFit an onlineforecast model with Recursive Least Squares...
rls_optimOptimize parameters for onlineforecast model fitted with RLS
rls_predictPrediction with an rls model.
rls_prmFunction for generating the parameters for RLS regression
rls_summaryPrint summary of an onlineforecast model fitted with RLS
rls_updateUpdates the model fits
rls_update_cppCalculating k-step recursive least squares estimates
rmseComputes the RMSE score.
scoreCalculate the score for each horizon.
setparSetting 'par()' plotting parameters
stairsPlotting stairs with time point at end of interval.
state_getvalGet the state value kept in last call.
state_setvalSet a state value to be kept for next the transformation...
step_optimForward and backward model selection
subset.data.listTake a subset of a data.list.
summary.data.listSummary with checks of the data.list for appropriate form.
summary.rls_fitPrint summary of an onlineforecast model fitted with RLS
onlineforecast documentation built on Oct. 12, 2023, 5:15 p.m.