double exponential smoothing

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Time Series mining-prediction algorithm-three exponential smoothing (holt-winters)-Three exponential smoothing algorithm can save the trend and seasonal information of time series data well

From:http://www.cnblogs.com/kemaswill/archive/2013/04/01/2993583.htmlIn the time series, we need to predict the following trend based on the current data of the time series, and the three exponential smoothing (Triple/three Order exponential smoothing,holt-winters) algorithm can predict the time series well.Time series

Prediction algorithm--exponential smoothing method

Directory? 1. Exponential smoothing definition and formula? 2. One-time exponential smoothing? 32-Times Exponential smoothing? 4. Three-times exponential

Time series mining-prediction algorithm-cubic exponential smoothing (Holt-Winters)

In a time series, we need to predict its future trend based on the existing data of the time series. The Three exponent Smoothing (Triple/Three Order Exponential Smoothing, Holt-Winters) the algorithm can well predict the time series. Time series data generally has the following characteristics: 1. Trend (Trend) 2. Seasonal (Seasonality ). The trend describes the

Exponential Smoothing, similarities, and differences mean (macd)

The exponential smoothing, similarities, and differences mean line (macd) is developed based on the moving average line. It uses two different speeds (a short-term moving average line with a fast change rate, the exponential smoothing moving average line of a long moving average line with a slow change speed is used to

[Original] streaminsight query series (23)-exponential smoothing of query modes

The previous article describes how to perform continuous updates in the query mode. This blog article describes how to implement exponential smoothing in streaminsight.Concepts Before implementation, let's take a look at what the exponential smoothing method is? Concepts: The expon

Reprint: Two times the Java code of the exponential smoothing method for predicting the value

Original address:Http://blog.csdn.net/qustmeng/article/details/52186378?locationNum=4fps=1Import java.util.LinkedList;Import java.util.List;public class Demo {/*** Two times exponential smoothing method for predicting values* @param list Base data collection* @param year of the next few installments* @param modulus Smoothing coefficient* @return Predictive value*

Calculate exponential smoothing and moving averages using Excel

Exponential Smoothing MethodThe original number data is as follows:Click Data--Data analysisSelect exponential SmoothingBest-in- one smoothingSince the area we selected was b1:b22, the first cell "steel output" was used as a sign, so we should tick the mark. When we tick the flag, the first cell in the column is not used for the calculation, and the calculation s

Exponential Smoothing Similarities and Differences moving average [macd]

Exponential Smoothing Similarities and Differences moving average[Macd] ■Exponential Smoothing Similarities and Differences moving average[Macd] -- it is an indicator constructed using two exponentially weighted moving averages. It can be us

R language and Data analysis eight: Holt exponential smoothing method

My friends and I shared the simple exponential smoothing method, simple exponential smoothing can only predict those at a constant level and no seasonal changes in the time series, today and you share the non-constant level of growth or reduce the trend, The time series prediction algorithm without seasonal additive mo

R Language and Data Analysis VII: Simple exponential smoothing of time series

We have a complete understanding of the time series sequence and decompose the time series, and today we share the simplest of the common predictive algorithms with the small partners: simple exponential smoothing. Simple exponential smoothing applies to the available additive model descriptions, and is at a constant l

R Language and Data Analysis IX: Holtwinters Exponential Smoothing method

Today goes on to the most complex time series in exponential smoothing: a predictive algorithm that has a time series of increasing or decreasing trends and having seasonal fluctuations is holt-winters and shared with everyone. This sequence can be decomposed into the horizontal trend part, the seasonal fluctuation part, therefore these two factors should have the corresponding parameter to control in the a

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