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47 lines
1.6 KiB
R
47 lines
1.6 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/prophet.R
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\name{add_seasonality}
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\alias{add_seasonality}
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\title{Add a seasonal component with specified period, number of Fourier
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components, and prior scale.}
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\usage{
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add_seasonality(m, name, period, fourier.order, prior.scale = NULL,
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mode = NULL, condition.name = NULL)
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}
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\arguments{
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\item{m}{Prophet object.}
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\item{name}{String name of the seasonality component.}
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\item{period}{Float number of days in one period.}
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\item{fourier.order}{Int number of Fourier components to use.}
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\item{prior.scale}{Optional float prior scale for this component.}
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\item{mode}{Optional 'additive' or 'multiplicative'.}
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\item{condition.name}{String name of the seasonality condition.}
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}
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\value{
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The prophet model with the seasonality added.
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}
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\description{
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Increasing the number of Fourier components allows the seasonality to change
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more quickly (at risk of overfitting). Default values for yearly and weekly
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seasonalities are 10 and 3 respectively.
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}
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\details{
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Increasing prior scale will allow this seasonality component more
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flexibility, decreasing will dampen it. If not provided, will use the
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seasonality.prior.scale provided on Prophet initialization (defaults to 10).
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Mode can be specified as either 'additive' or 'multiplicative'. If not
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specified, m$seasonality.mode will be used (defaults to 'additive').
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Additive means the seasonality will be added to the trend, multiplicative
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means it will multiply the trend.
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If condition.name is provided, the dataframe passed to `fit` and `predict`
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should have a column with the specified condition.name containing booleans
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which decides when to apply seasonality.
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}
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