Commit | Line | Data |
---|---|---|
46952971 BA |
1 | % Generated by roxygen2: do not edit by hand |
2 | % Please edit documentation in R/getForecast.R | |
3 | \name{getForecast} | |
4 | \alias{getForecast} | |
5 | \title{get Forecast} | |
6 | \usage{ | |
7 | getForecast(data, indices, forecaster, pjump, memory = Inf, | |
8 | horizon = data$getStdHorizon(), ...) | |
9 | } | |
10 | \arguments{ | |
11 | \item{data}{Dataset, object of type \code{Data} output of \code{getData}} | |
12 | ||
13 | \item{indices}{Days indices where to forecast (the day after)} | |
14 | ||
15 | \item{forecaster}{Name of the main forcaster | |
16 | \itemize{ | |
17 | \item Persistence : use values of last (similar, next) day | |
18 | \item Neighbors : use values from the k closest neighbors' tomorrows | |
19 | \item Average : global average of all the (similar) "tomorrow of past" | |
20 | \item Zero : just output 0 (benchmarking purpose) | |
21 | \item Level : output a flat serie repeating the last observed level | |
22 | }} | |
23 | ||
24 | \item{pjump}{How to predict the jump at the interface between two days ? | |
25 | \itemize{ | |
26 | \item Persistence : use last (similar) day values | |
27 | \item Neighbors: re-use the weights optimized in corresponding forecaster | |
28 | \item Zero: just output 0 (no adjustment) | |
29 | }} | |
30 | ||
31 | \item{memory}{Data depth (in days) to be used for prediction} | |
32 | ||
33 | \item{horizon}{Number of time steps to predict} | |
34 | ||
35 | \item{...}{Additional parameters for the forecasting models} | |
36 | } | |
37 | \value{ | |
38 | An object of class Forecast | |
39 | } | |
40 | \description{ | |
41 | Predict time-series curves for the selected days indices (lines in data). | |
42 | } | |
43 | \examples{ | |
44 | data = getData(ts_data="data/pm10_mesures_H_loc.csv", exo_data="data/meteo_extra_noNAs.csv", | |
45 | input_tz = "Europe/Paris", working_tz="Europe/Paris", predict_at=7) | |
46 | pred = getForecast(data, 2200:2230, "Persistence", "Persistence", 500, 12) | |
47 | \dontrun{#Sketch for real-time mode: | |
48 | data = new("Data", ...) | |
49 | forecaster = new(..., data=data) | |
50 | repeat { | |
51 | data$append(some_new_data) | |
52 | pred = forecaster$predict(data$getSize(), ...) | |
53 | #do_something_with_pred | |
54 | }} | |
55 | } | |
56 |