How to Use InfluxDB’s Holt-Winters Function for Predictions

Welcome to Part Three of this three-part blog post series. To understand Part Three, I suggest reading Part One and Two first.

In Part One, we covered:

1. When to use Holt-Winters
2. How Single Exponential Smoothing works
3. A conceptual overview of optimization for Single Exponential Smoothing
4. Extra: The Proof for Optimization of RSS for Linear Regression

In Part Two, we dove into:

1. How Single Exponential Smoothing relates to Triple Exponential Smoothing/Holt-Winters
2. How RSS relates to RMSE (root mean squared error)
3. How RMSE is optimized for Holt-Winters using the Nelder-Mead method

In Part Three, we explore:

1. How you can use InfluxDB’s built-in Multiplicative Holt-Winters function to generate predictions on your time series data
2. A list of learning resources

How to use InfluxDB’s built-in multiplicative Holt-Winters function to generate predictions on time series data

For the sake of Developer Experience, I’ve decided to follow the Holt-Winters example in the documentation. The dataset for this example can be downloaded with:

curl https://s3.amazonaws.com/noaa.water-database/NOAA_data.txt -o…