Questions tagged [exponential-smoothing]

A basic forecasting technique for time series data, optionally including trend and/or seasonality, but (usually) excluding causal influences.

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16
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3answers
16k views

ETS() function, how to avoid forecast not in line with historical data?

I am working on an alogorithm in R to automatize a monthly forecast calculation. I am using, among others, the ets() function from the forecast package to calculate forecast. It is working very well. ...
12
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3answers
7k views

Ensemble time series model

I need to automate time-series forecasting, and I don't know in advance the features of those series (seasonality, trend, noise, etc). My aim is not to get the best possible model for each series, ...
12
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1answer
8k views

When to use Exponential Smoothing vs ARIMA?

I have recently been refreshing my forecasting knowledge while working on some monthly forecasts at work and reading Rob Hyndman's book but the one place I am struggling is when to use an exponential ...
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3answers
13k views

Use Holt-Winters or ARIMA?

My question is around the conceptual difference between Holt-Winters and ARIMA. As far as I understand, Holt-Winters is a special case of ARIMA. But when is one algorithm preferred over the other? ...
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4answers
19k views

R time-series forecasting with neural network, auto.arima and ets

I've heard a bit about using neural networks to forecast time series. How can I compare, which method for forecasting my time-series (daily retail data) is better: auto.arima(x), ets(x) or nnetar(x)....
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1answer
6k views

Standard Deviation of an Exponentially-weighted Mean

I wrote a simple function in Python to calculate the exponentially weighted mean: ...
7
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2answers
729 views

Problem with proof - why exponentially smoothed time series is biased

I'm working through the proof why the exponential smoothing is a biased estimator of a linear trend. The book is trying to describe the expected value of an exponentially smoothed time series. It's ...
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2answers
7k views

Time series prediction: Neural Network (nnetar) vs. exponential smoothing (ets)

When I make a forecast for the univariate time series $x_1=1, x_2=2, \dots, x_{14} = 14$, why does the nnetar() function in R (which uses a neural network) not ...
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2answers
6k views

Avoid negative results in Holt Winters forecasting

I understood that Holt Winters forecasting may results in negative values due to trending. I did reduce trending component value, but still forecast values are negative territory. Our data set will ...
7
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3answers
11k views

Forecasting beyond one season using Holt-Winters' exponential smoothing

I am using the Holt-Winters' exponential smoothing technique to forecast expenditure data 2 years into the furture. The monthly data has an increasing trend and annual seasonality. I'm using MS Excel ...
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3answers
3k views

Tuning an exponential moving average to a moving window mean?

The alpha parameter of an exponential moving average defines the smoothing that the average applies to a time series. In a similar way, the window size of a moving window mean also defines the ...
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1answer
12k views

Explain the croston method of R

I am using crost() function of R for analyzing and forecasting intermittent demand/slow moving items time series. I am having difficulty in understanding the output....
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5answers
14k views

What do the “coefficients” in R's HoltWinters function represent?

I'm using the HoltWinters function in R and I'm trying to understand what the "coefficients" represent in the object that is returned by that function. They don't seem to match in any obvious way the ...
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4answers
1k views

Choice of time-series model for store sales prediction

I have a data set of weekly sales for a range of stores (all belonging to one company). I am trying to predict weekly/monthly use of several ingredients in the individual stores. The choice for what ...
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3answers
15k views

How to use triple exponential smoothing to forecast in Excel

I have been burdened with the task of coming up with a forecast plan for my company. I have no experience and am VERY new to the whole forecasting scene. As of right now, my company has no plans of ...
5
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1answer
324 views

Robust alternative to exponential smoothing?

Despite being easy to calculate and understand, exponential smoothing is excessively affected by outliers and thus performs poorly when the data has a non-Gaussian probability distribution, such as a ...
5
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1answer
16k views

Interpretation of level, trend and seasonal indices in Holt-Winters exponential smoothing

I am trying to learn Holt-Winters exponential smoothing. In the algorithm there are three indices involved (level, trend, ...
5
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1answer
2k views

Predicting temperature time series with Holt-Winters

I am trying to write a prediction algorithm for a set of temperature data. I settled on Holt-Winters since it seemed to be a simple time series prediction algorithm and I can easily code it up in ...
5
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1answer
7k views

Need clarity on alpha, beta, gamma optimization in Triple Exponential Smoothing Forecast

I asked a variation of this question, but I want to be more direct. Take the exact same Triple Exponential Smoothing Model (Holt-Winters with a moving level, trend, and seasonal component)--- Would ...
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0answers
1k views

Best practices for dealing with shifting, inconsistent seasonality

This question is related to a previous post I've looked at (Calculation of seasonality indexes for complex seasonality), but deals with more granular data (daily instead of weekly), and transforming ...
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5answers
2k views

Is it always required to achieve stationarity before performing any time-series analysis?

For example, I know that for ARIMA models stationarity needs to be achieved. What about Exponential Smoothing? Is it also required?
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2answers
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Confusing Holt-Winters parameters

I have got a model for forecasting using holt-winters. However the parameters confuse me... The parameters show that there is no trend or seasonality even though there is definite trend and ...
4
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1answer
688 views

Are both ARIMA and Exponential Smoothing special cases of State Space models?

From the literature I gather that exponential smoothing models can be recast as special cases of state space models. I haven't seen similar references w/r to ARIMA being considered state space models,...
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2answers
2k views

Moving Average, Exponential Smoothing, and Random Walk for Forecasting

I would like to confirm my understanding. Is it true that a (simple) exponential smoothing model with alpha (smoothing constant) = 1 is the same as MA(1), which is in turn the same as a random walk ...
4
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3answers
9k views

Forecast daily data with weekly and monthly seasonality using exponential smoothing

I have to forecast data that exhibits dual seasonality. For example, the first day of the week can show seasonality and also the first week of the month can show seasonality. I am planning to use ...
4
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2answers
4k views

Confidence intervals for exponential smoothing

I'm using exponential smoothing (Brown's method) for forecasting. The forecast can be calculated for one or more steps (time intervals). Is there any way to calculate confidence intervals for such ...
4
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1answer
996 views

Holt-Winters Forecasting - Why do we use most recent estimate for all projections going forward?

I've been doing some research on using the Holt-Winters method for forecasting and understand all but one aspect. Why do we use the most recent estimate for the base and trend components for all ...
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2answers
3k views

Exponential smoothing models backcasting and determining initial values python

I have made python code for exponential smoothing (ES) that takes in about 15 different cases including: Simple Exponential Smoothing (SES) Simple Seasonal models (both multiplicative and additive) ...
4
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3answers
7k views

Holt-Winters and Abnormal termination in LNSRCH

I try to fit data with Holt-Winters function in R. Nevertheless, i am getting the following message: ...
4
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2answers
3k views

Using exponential smoothing to forecast irregularly spaced data in R

I'd like to use exponential smoothing to forecast the following data. The data is daily based. Because of some policy reasons, every $29^\text{th}$, $30^\text{th}$ and $31^\text{th}$ of each month, ...
4
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1answer
229 views

Equivalence between some Exponential Smoothing methods and ARIMA

I read from a few sources that certain exponential smoothing methods (linear state-space) have an equivalence form as ARIMA. For example, simple exponential smoothing (SES) as ARIMA(0,1,1) and Holt's ...
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2answers
977 views

simple exponential smoothing with drift

I have researched all over the text books and software (R/SAS/SPSS), but I have not encountered Simple Exponential Smoothing (SES) with a drift ? Is it possible to add a drift term to Simple ...
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1answer
1k views

How 'good' are Holt-Winters forecasts with unusual alpha, beta and gamma values?

I'm using this python script for Holt-Winters forecasting (https://gist.github.com/andrequeiroz/5888967) that I believe chooses values of alpha, gamma and beta via RMSE optimisation. Sometimes the ...
4
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1answer
3k views

Holt-Winters exponential smoothing formula

I am trying to implement Holt-Winters exponential smoothing in Java program (I understand that R and Python have implementations of these algorithms, but I can't use those due to other reasons, so ...
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3answers
7k views

Non-Stationary Time Series Forecasting

Suppose I have a non-stationary limited data. Do I have to make it stationary before making forecasts? Can I use exponential smoothing, moving averages or even Holt Winters methods without making my ...
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3answers
1k views

Definition of the function for exponentially decaying weighted average

I feel really thick asking this question, but I'm afraid I don't really understand the Wikipedia article explaining how to do a weighted average with expontentially decreasing weights. I really have ...
3
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3answers
3k views

Alternatives to Using ARIMA for forecasting

I've been dealing with mostly univariate time series data and am wondering what alternative models exist for forecasting instead of ARIMA, ARMA, AR and MA processes, I know about exponential ...
3
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1answer
3k views

Does the Holt-Winters algorithm for exponential smoothing in time series modelling require the normality assumption in residuals?

I'm working on a project to compare different approaches to time series modeling. In the model selection process, we perform residual analysis for the fitted models. For regression, we need to check ...
3
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1answer
4k views

R-squared to compare forecasting techniques

Is it appropriate when forecasting to use $R^2$ as the measure of how well exponential smoothing fits a data set for the purpose of time-series forecasting? I understand that it is appropriate for ...
3
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1answer
769 views

In triple exponential smoothing, what is the proper formula for recalculating gamma (seasonality)?

A pretty targeted but precise question -- In triple exponential smoothing (which there are many combinations of additive, multiplicative). What is the proper formula for calculating the new ...
3
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1answer
205 views

What data generation process corresponds to exponential moving average prediction?

For each ARMA process formulation, there is an optimal prediction. E.g.: When you believe that $y_{t+1}=\alpha y_t + \varepsilon_{t+1}$, where $\varepsilon_{t+1}$ are IID, you predict $\hat{y}_{t+1}=\...
3
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1answer
547 views

Exponential smoothing method that can be used in seasonal forecasting without trend

I'm working on the task of forecasting. The data I have is seasonal. I use exponential smoothing methods, but my references (e.g. for the Holt-Winters method) are for using such methods for seasonal ...
3
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1answer
979 views

Best way to deal with forecasting with noisy data?

I have a bunch of sales data. It is from distributors of 2000 different items, who service big companies and large distributors to a number of small independent stores. They sell some items which do ...
3
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1answer
9k views

Which is the better method to do forecast..1-step or h-step ahead?

I am using forecast() package in R to predict future values. I have a time series data for approx 6-7 years. First, I split the data into training set and test set. Test set contained values of the ...
3
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1answer
318 views

R - Holt-Winters - irregular frequency

I originally posted this on Stack Overflow, and it was suggested that this question would be better suited for CV: With reference to the HoltWinters function in R, how does one deal with time ...
3
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1answer
1k views

Seasonal or non-seasonal? ETS and auto-arima disagree?

I am working with the following monthly time series to build forecasting models: From this plot, it's quite tricky to identify if there is some kind of seasonality or not. When I use the ...
3
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1answer
218 views

Dealing with extreme shocks like global recession in time series

I'm following Rob Hyndman's forecasting otext to practice on some financial data for fun and I am having difficulties in trying to properly deal with large shocks similar to the 2008 recession. My ...
3
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1answer
312 views

Exponential smoothing versus GARCH(1,1) for conditional variance

I have a panel data of stock returns and I want to estimate the covariance matrix of these returns throughout time. I also want to use exponential smoothing. The scheme is as follows. $$\hat{\Sigma}...
3
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1answer
709 views

Residuals in double seasonal exponential smoothing

I have a time series with muliple seasonal cycles, which are 24 and 168 hours for my case. I would like to use Double Seasonal Exponential Smoothing method to forecast, which was published by James W. ...
3
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0answers
118 views

How to learn beta in (this)variation of Brown's Simple Exponential Smoothing?

I have the below equation: Y' = Y + β Y1 + β^2 Y2 + β^3 Y3 This is time-series data where ...