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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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52 views

Can I say Holt-Winters Method is an example of interpolation?

I believe it fits under the definition from wiki: In the mathematical field of numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of ...
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502 views

Implementation Difference between HoltWinters and hw functions of R's forecast package

While searing for examples for implementing Holtwinters with R, I came across following two functions: hw function from forecast package HoltWinters function from R-Core For the same data set, ...
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287 views

Automatic forecasting in R discrepancy

I am new to time series forecasting and I am trying to understand automatic forecasting algorithm in the forecast package in R. I read http://www.jstatsoft.org/v27/i03 this paper and I tried to run: ...
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Solving for arima and exponential smoothing coefficients

I am looking to How do you solve for the optimum values with the lowest MSE for the coefficients and dampening constant in exponential smoothing and ARIMA models? What are the equation used?
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Holt-Winters and importance of R-square

Is R-square an important measure in Holt-Winters method?
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295 views

Initialization and estimation in exponential smoothing

Following Eqs. (3.10a) and (3.10b) from (Hyndman et al., 2008) I obtained a simulated series $y_t=l_{t-1}+\varepsilon_t$ and level $l_t=l_{t-1}+\alpha\,\varepsilon_t$, $t=1.2,\ldots,40$, see data ...
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Possible issues using moving average as an input for exponential smoothing?

I'm currently working with an ERP system that applies Exponential Smoothing to what it defines as "demand," which is itself a simple 90-day moving average of sales. I initially didn't trust it ...
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why is the level equation in the holt winters triple exponential model different from the other two?

the double exponential model is so simple: level: $s_t = \alpha x_t + (1-\alpha)(s_{t-1}+b_{t-1})$ trend: $b_t = \beta (s_t - s_{t-1}) + (1-\beta)b_{t-1}$ both intuitively weigh the new information ...
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Search for optimal alpha in EWMA

All literature about finding the best alpha for a EWMA points to use RMSE to measure the fit between the EWMA and the signal. As alpha increases, the series get less and less smoothed out, and as a ...
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462 views

Applying EWMA to first difference of a time series

I am trying to fit an EWMA to the first difference but I am unsure how to properly fit the EWMA and how to assess if one model is better than another. I am trying to use the EWMA described in the <...
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514 views

Techniques to improve accuracy of time series use case

I am working on forecasting weekly revenue of 10,000 sectors. Applied basic time series models and average RMSE(in thousands) on hold-out set (last 32 weeks) as below. In my view, ma12 and ETS(ANN) ...
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How to select between Holt Winters Model and ARIMA

I need to do sales forecasting.My historical data shows stationary pattern & present of trend,Seasonality & cyclic pattern. I would like to check with you that how to select between Holt ...
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411 views

Inverse of exponential smoothing

Suppose that a time series $s_t$ it is known to be obtained via exponential smoothing of an underlying signal $x_t$, that is $$ s_{0}= x_0 $$ and $$ s_{t} = (1-\alpha)\,x_t+\alpha\,s_{t-1}. $$ ...
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247 views

Why do my weights have to equal one?

I'm currently learning the very basics of exponential smoothing. As follows: The book first presents the following model: $$\sum{\theta^tY_{T-1}}$$ It then claims that the sum of all weights add ...
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How to choose automatically between Auto.ARIMA, ETS and STL in R

I'm working on a sales forecasting package which should be easy to use for the end user. Given a time series with historical sales data I would like to automatically select one of the three forecasts: ...
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156 views

Efficient automated prediction for a 1000 growing, big data sets. How to?

I have daily data points of the number of sales, but I am not looking at historic data only. My system delivers a new data point every day and in the evening I want to predict the number of sales ...
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257 views

How can I calculate the PI of (simple) exponential smoothing?

I would like to calculate the prediction intervals of exponential smoothing. In R there is a function (ses in a forecast package) which calculates the point forecast and also the prediction intervals. ...
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Time series Exponential smoothing by Holt winters method

I have basic questions with respect to exponential smoothing techniques, from statsmodels.tsa.holtwinters import ExponentialSmoothing add_model = ExponentialSmoothing(traindata,seasonal_periods=12 ,...
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Forecasting method for different cohorts with large seasonal swings but otherwise stable data

I am attempting to forecast percentage of churn for different cohorts. However, I am unsure how to proceed after selecting an initial method. The churn is fairly stable except for large seasonal ...
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Is Box-Jenkins approach to time-series prediction and forecasting similar to Unobserved Components models approach?

How I understand the Box-Jenkins Method in a nut-shell is that a time-series model has signals that can be identified by weighting its own past lagged values, or weighting its owned past errors or ...
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Hyperparameter-free method for Moving Average/ Exponential smoothing?

I want to find hyperparameter-free method for Moving Average/ Exponential smoothing. Is there any related paper or python code? S(t)= alpha * F(t) + (1-alpha) * S(t-1) Any methods can avoid the ...
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Question about the weighting factor of Exponential Weighted Moving Average (EWMA/EMA)

Hiii, I have one question about the weighting factor of EMA. As I learned, Exponential Weighted Moving Average has a weighting factor, Lamda, and its formula is: S(t) = Lamda * Y(t) + (1-Lamda) * S(...
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Closest ARIMA models to Holt-Winter's Mixed Model and Time Series Decomposition Models

Can you please tell which ARIMA model will be closest to Holt-Winter's mixed model and Time Series Decomposition (additive/multiplicative) models And that ARIMA model maybe used in replacement of the ...
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How to get a forecast equation for $\hat{y}$ using ETS state space model

The ets(AAA) state space model (Rob Hyndman's handbook) is as below State equation is \begin{equation} Y_t = L_{t-1} + b_{t-1} + S_{t - m} + \varepsilon_t \end{equation} The measurement equations ...
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Holt-winters method, outlier day of week

Hopefully this isn't too off topic. I've just received test results and disagree with some explanations of a question. The TA and I can't seem to resolve our differences and I'm starting to think ...
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What is the best calculation method to account for individual change, volatility, observation windows and time decays in time series data? ARIMA, ETS?

I am looking at applying a theoretical best calculation method to some particular time series (ts) data. Ideally the calculation method would encompass relative change in individual ts, volatility of ...
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How to forecast individual customer's spend (for millions of customers)?

Which forecasting model fits better to forecast the customers spend in the next upcoming visit? We have millions of customers, so ARIMA or any other time series modeling for each of the customers is ...
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When we are proving why ARIMA(0,1,1) is equal to simple exponential smoothing, why can we considered theta to be equal to (1-alpha)

I know this is a very basic question, but its not clarified within my lectures. Essentially when you have ARIMA(0,1,1) You can simplify the theta 1 term in order to obtain SES via stating its (1-...
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Historical average with exponential smoothing model [duplicate]

This topic similar with this one R Time Series Analysis forecast result always remains same But I perfrom exponential smoothing model in R. ...
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213 views

Strange output while using Holt’s Linear Trend method

Here're the pictures of using Holt’s Linear Trend method: From tutorial (what it should be like): After running the code for my data Isn't it strange? Here's a code (method #5): ...
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What are the prerequisites before running Holt Winters Model?

I just read Demand-Driven Forecasting: A Structured Approach to Forecasting(Wiley and SAS Business Series) and have a few doubts in Holt-Winters Model: 1) Unlike OLS Regression Modeling technique or ...
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How to calculate the average age of observations in forecasting models of various types?

Suppose you have a time series $\ Z_t$ that is used as a forecasting model for $\tau$ steps ahead from origin $T$. $\ Z_t$ is defined as: $\ Z_t = 0.05 Z_T + 0.10 Z_{T-1} + 0.15 Z_{T-2} + 0.20 Z_{T-...
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Forecasting methods to work globally on a series of datasets

Forecasting a numeric time-series is providing an estimator $\hat y(t+1)$ of $y(t+1)$ computed from $(y(1),y(2)...y(t))$. You want it to be close to $y(t+1)$ (say in terms of squared distance). Now ...
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How to solve or choose the smoothing parameter phi in solving for the Nonlinear trend exponential smoothing?

In forecasting, to solving for the nonlinear trend exponential smoothing can you just choose any value of ϕ or is there a way to solve for it?
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Excel FORECAST.ETS What method based on?

Excel offers an exponential smoothing function. I currently use Excel 2013. In the Documentation it says: Calculates or predicts a future value based on existing (historical) values by using the ...
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Appropriate forecasting model [duplicate]

I only have 2 available points and I wish to forecast its value for the next year. I'm currently looking into exponential smoothing, and econometric input-output model. Which one would be more ...
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2answers
186 views

Will ARIMAX or exponential smoothing forecast a short time series better?

The objective requires to predict GROSS NPA for 6 months and provided with 2 years of data i.e., around 24 observations. So, which of the method will provide better forecast?
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Advance Methods of Understanding Significance of Customer Behaviors

I currently own a couple of websites and lately I've been implementing some feature changes - I've noticed some changes in website traffic and I was wondering what some of the more sophisticated ways ...
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402 views

ETS or ARIMA model

I have a time series data set and want to predict my data in the future. I would like to when to use a ETS or an ARIMA model? Is is true that you can only use a ETS model when a data is non-...
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Usage of AIC for comparing models [duplicate]

Can AIC be used to compare a model with exponential smoothing with linear regressions?
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552 views

Using a stationary data set with exponential smoothing

I am doing time series forecasting and running Holts Method with several variations.(exponential, damped, simple) ...
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393 views

simple exponential smoothing - Ljung-Box test - residual

While reading this page on time series I found this sentence: The Ljung-Box test showed that there is little evidence of non-zero autocorrelations in the in-sample forecast errors, and the ...
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195 views

Adding predictor variables and/ or systematic judgement to time series forecasts

I have a ways to go with my forecasting general education --- but I'm doing a seasonal time-series forecast for predicting sales order volumes. It's mostly software sales, which does have a ...
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253 views

Statistical demand forecasting

How is batch demand forecasting done in retail like in Walmart where number of products to forecast are very large in number and products are short lived i.e have less than 36 months of historical ...
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1answer
1k views

Anomaly detection using exponential weighted moving average

I would like to detect anomaly using exponential weighted moving average. I don't have series of data points. All I have is EMA(t-1) and the data point of the current time(t) DP(t). From these data, ...
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414 views

Help choosing the optimal time series analysis package

I am developing an app for time series analysis that should support the following: Exponential Smoothing (Holt-Winters) Box-Jenkins curve fitting (straight line, quadratic, exponential, growth) ...
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1answer
264 views

How to align two seasonal time series

I am trying to decompose a time series using Holt Winters method and use it for forecast. I am trying to do this for weekly data of last 25-26 months. The challenge is that the dates of the seasonal ...