ATA.Forecast: Forecasting Time Series Using the ATA Method

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/ATA_Forecast.r

Description

ATA.Forecast is a generic function for forecasting of the ATA Method.

Usage

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ATA.Forecast(
  object,
  h = NULL,
  out.sample = NULL,
  ci.level = 95,
  negative.forecast = TRUE
)

Arguments

object

An ATA object is required for forecast.

h

Number of periods for forecasting.

out.sample

A numeric vector or time series of class ts or msts for out-sample.

ci.level

Confidence Interval levels for forecasting. Default value is 95.

negative.forecast

Negative values are allowed for forecasting. Default value is TRUE. If FALSE, all negative values for forecasting are set to 0.

Value

An object of class "ATA".

Author(s)

Ali Sabri Taylan and Hanife Taylan Selamlar

References

Yapar, G., (2016) "Modified simple exponential smoothing" Hacettepe University Journal of Mathematics and Statistics Early Access. Doi:10.15672/HJMS.201614320580

Yapar, G., Capar, S., Selamlar, H. T., Yavuz, I., (2016) "Modified holt's linear trend method" Hacettepe University Journal of Mathematics and Statistics Early Access. Doi: 10.15672/HJMS.2017.493

See Also

forecast, stlplus, stR, stl, decompose, tbats, seasadj.

Examples

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ata.fit <- ATA(M3[[1899]]$x, M3[[1899]]$xx)
fc <- ATA.Forecast(ata.fit, h=18)

alsabtay/ATAforecasting documentation built on Dec. 1, 2019, 5:26 a.m.