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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/diagnostics.R
\name{cross_validation}
\alias{cross_validation}
\title{Cross-validation for time series.}
\usage{
cross_validation(
model,
horizon,
units,
period = NULL,
initial = NULL,
cutoffs = NULL
)
}
\arguments{
\item{model}{Fitted Prophet model.}
\item{horizon}{Integer size of the horizon}
\item{units}{String unit of the horizon, e.g., "days", "secs".}
\item{period}{Integer amount of time between cutoff dates. Same units as
horizon. If not provided, 0.5 * horizon is used.}
\item{initial}{Integer size of the first training period. If not provided,
3 * horizon is used. Same units as horizon.}
\item{cutoffs}{Vector of cutoff dates to be used during
cross-validtation. If not provided works beginning from (end - horizon),
works backwards making cutoffs with a spacing of period until initial is
reached.}
}
\value{
A dataframe with the forecast, actual value, and cutoff date.
}
\description{
Computes forecasts from historical cutoff points which user can input.If
not provided, these are computed beginning from (end - horizon), and working
backwards making cutoffs with a spacing of period until initial is reached.
}
\details{
When period is equal to the time interval of the data, this is the
technique described in https://robjhyndman.com/hyndsight/tscv/ .
}
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