Forecasting using Holt-Winters technique using R with less than 2 years of history

Question

I need to do forecasting of weekly sales using Holt-Winters technique. My data have max 92 weeks of information. I'm planning to consider 72 weeks of data for training & 20 weeks of data for validation & I have only available s/w to do the forecast is R. I'm preparing my training & validation data set using following command

data_ts_s = ts(data$SUM.SALES_UNITS.[c(1:72)], frequency=52)
data_ts_c = ts(data$SUM.SALES_UNITS.[c(73:92)], frequency=52)

But for doing forecast using HW, R needs at least 2 periods of data. Can you please help me how to do the forecasting with Holt-Winters technique without 104 weeks of data.

Answer 1

The Holt-Winters method is a poor choice for weekly data. It involves estimating a parameter for each week so the model has far too many degrees of freedom.

One approach which should work ok is to use a TBATS model which uses Fourier terms for the seasonality, and so requires fewer coefficients. In your case:

library(forecast)
fit <- tbats(data_ts_s)
fc <- forecast(fit, h=20)

The TBATS model is a generalization of the Holt-Winters approach.