Weighted Moving Average (WMA) – Smoothing
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.
Read through the articles below to stay up to date with NumXL Pro and topics related to time series, statistics, modeling, forecasting, and many more.
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.
This article includes he data preparation aspect of time series analysis we start with the sampling assumptions of the time series.
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.
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