Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [exponential-smoothing]

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

256 questions
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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. Unfortunately, for some specific time series, the…
mehdik
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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, but to avoid pretty bad models. In other words, to…
João Daniel
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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 smoothing model vs an ARIMA model. Is there a…
user1723699
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Standard Deviation of an Exponentially-weighted Mean

I wrote a simple function in Python to calculate the exponentially weighted mean: def test(): x = [1,2,3,4,5] alpha = 0.98 s_old = x[0] for i in range(1, len(x)): s = alpha * x[i] + (1- alpha) * s_old s_old = s return s However,…
Mariska
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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? Perhaps Holt-Winters is incremental and therefore…
sandyp
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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). I can compare auto.arima with ets by AIC or BIC.…
Jurgita
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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 smoothing. Is there some way to tune the alpha parameter…
naught101
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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 one of these steps I'm having trouble…
Magnus
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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. Could anyone help in understanding the model in layman's terms. Below is the code…
Arushi
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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 values returned when you look at the $
RicLouRiv
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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 type of model to use seems to be between Holt…
pApaAPPApapapa
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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 never be in negative values (like electricity data…
kosa
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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 with the Solver add-in to calculate the optimal…
Elizabeth
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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 calculate correct results, whereas ets() (which uses exponential smoothing)…
flobrr
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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, seasonality) while forecasting. My questions: What is the interpretation of these 3 indices? How do I differentiate between…
user2409011
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