VisitorCounts (version 2.0.3)

predict.decomposition: Predict Decomposition

Description

Methods for generating predictions from objects of the class "decomposition".

Usage

# S3 method for decomposition
predict(object, n_ahead, only_new = TRUE, ...)

Value

forecasts

A vector with overall forecast values.

trend_forecasts

A vector with trend forecast values.

seasonality_forecasts

A vector with seasonality forecast values.

Arguments

object

An object of class "decomposition".

n_ahead

An integer describing the number of forecasts to make.

only_new

A Boolean describing whether or not to include past values.

...

Additional arguments.

Examples

data("park_visitation")
suspected_periods <- c(12,6,4,3)
proportion_of_variance_type = "leave_out_first"
max_proportion_of_variance <- 0.995
log_ratio_cutoff <- 0.2

park <- "DEVA"

nps_ts <- ts(park_visitation[park_visitation$park == park,]$nps, start = 2005, freq = 12)
nps_ts <- log(nps_ts)

pud_ts <- ts(park_visitation[park_visitation$park == park,]$pud, start = 2005, freq = 12)
pud_ts <- log(pud_ts)

nps_ts <- ts(park_visitation[park_visitation$park == park,]$nps, start = 2005, freq = 12)
nps_ts <- log(nps_ts)

decomp_pud <- auto_decompose(pud_ts,
                                     suspected_periods,
                                     proportion_of_variance_type = proportion_of_variance_type,
                                     max_proportion_of_variance,
                                    log_ratio_cutoff)
n_ahead = 36
pud_predictions <- predict(decomp_pud,n_ahead = n_ahead, only_new = FALSE)