Jump to content

Holt Winters Forecasting Data Function for Spotfire® 2.0.0


2 Screenshots

Summary

Univariate time-series preparation and modeling with Holt-Winters smoothing and forecast.

Overview

This data function applies the Holt Winters method to calculate fit and forecast over a univariate time series.

Starting from Release 2.0.0, the input time series dataset can be pre-processed in a separate data function (Preprocess Time Series) to prepare inputs for Holt Winters. Data aggregation, periodicity analysis and missing data imputation is thus made possible. A test dataset can optionally be added, to get an idea of how the forecast would match actual values. 

Written in R code. Packages required: data.table, zoo, lubridate.

More details about this data function can be found in this community article.

 

Installing the data function

Follow the online guide available here to register a data function in Spotfire.

 

Configuring the data function

Each data function may require inputs from the Spotfire analysis and will return outputs to the Spotfire analysis. For each data function, these need to be configured once the data function is registered. To learn about how to configure data functions in Spotfire please view this video:

For more information on Spotfire visit the Spotfire training page.

 

Data function library

There exists a large number of data functions covering various features. Feel free to review what is available on the Data Function Library

Release 2.0.0

Published: February 2024

Changes to previous release:

  • Bug fixes
  • Added:
    • Preprocessing Time Series data function with periodicity analysis, aggregation and missing data imputation.
    • Smoothing of existing Training dataset
    • Optional Test dataset
    • Example Spotfire dxp and Community article.

 

Initial Release (version 1.1.0)

Published: January 2023

Initial release includes:

  • Data function
  • Documentation
  • License information

×
×
  • Create New...