Simon Fraser University

Equations for the Smoothing Models

The ARIMA model equivalency to the additive version of Winters method is the ARIMA(0,1,p+1)(0,1,0) p model The moving-average form of the equation is For the additive version of Winters method (see ...
Harvard Business School

Quantile Forecasts of Product Life Cycles Using Exponential Smoothing.

Guo, Xiaojia, Kenneth C. Lichtendahl Jr., and Yael Grushka-Cockayne. "Quantile Forecasts of Product Life Cycles Using Exponential Smoothing." Harvard Business School Working Paper, No. 19-038, October ...
Simon Fraser University

Forecasting Methods

In the STEPAR method, PROC FORECAST first fits a time trend model to the series and takes the difference between each value and the estimated trend. (This process is called detrending.) Then, the ...
Harvard Business School

A Two-Stage Forecasting Model: Exponential Smoothing and Multiple Regression

Crane, D. B., and James R. Crotty. "A Two-Stage Forecasting Model: Exponential Smoothing and Multiple Regression." Management Science 13, no. 8 (April 1966).
ascopubs.org

Time Series Prediction of Lung Cancer Death Rates on the Basis of SEER Data

This study used SEER data from 1975 to 2018 and included 545,486 patients with lung cancer. The best parameters for ARIMA are ARIMA (p, d, q) = (0, 2, 2). In addition, the best parameter for SES was α ...
Houston Chronicle

Statistical Methods of Sales Forecasting

Various statistical forecasting methods exist designed for use with slow-moving products, new product introductions, stable mature products and products with erratic demand. Determining which ...