Read through the articles on smoothing functions and algorithms for time series.
NumXL 1.66 is released. The new release includes several new features: support for non-parametric data-fitting modeling, Two-dimensional interpolation, and several time-series smoothing and filtering functions.
In this article, we will demonstrate the use of the WMA function in NumXL to smooth out time-series data and create a sample forecast.
In this article, we’ll demonstrate some examples to show the Brown’s Simple Exponential Smoothing function in NumXL.
In this article, we’ll show some examples to demonstrate Holt’s Double Exponential Smoothing function.
In this article, we’ll show some examples to demonstrate Brown’s Linear Exponential Smoothing function.
In this article, we’ll show some examples to demonstrate Holt-Winters’ Triple Exponential Smoothing function.
This week, we go over time series smoothing functions, highlight its assumptions and parameters, and demonstrate its application through examples. Why should we care? Smoothing
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