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

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13 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 ...
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0answers
18 views

Disadvantages of Holt-Wínters model [on hold]

What do you think, what are the disadvantages of Holt-Winters model? I cannot google any clear answer
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0answers
8 views

Formula to estimate parameter in double seasonal exponential smoothing

I have read the Taylor's Journal of double seasonal exponential smoothing, in his journal he said that the parameter of double seasonal exponential smoothing is estimate by the common procedure of ...
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1answer
46 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 ...
0
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1answer
43 views

R times series — correct use of forecast() and accuracy() in forecast package

Cross-posting this from Stack Overflow, because it's a bit of a stats/ technology cross-over. I'm relatively new to R and the forecast package I believe authored by Rob Hyndman. I'm having trouble ...
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0answers
28 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 ...
0
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1answer
73 views

Maximum Likelihood Estimator for Exponential Smoothing

I'm not a statistician, so I would love an easy to understand answer. Is there a maximum likelihood estimator that can be stated as an explicit function of the observed data for the models enumerated ...
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0answers
25 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 ...
2
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0answers
47 views

Exponentially Weighing Moving Average (EWMA) for weekly data

I'm aware that the typical EWMA approach is applied over larger time periods (say for Volatility, where lambda = 94% and all weights add up to 100% for stock returns data from last 5 years). ...
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33 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 ...
3
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1answer
94 views

Standard Deviation of an Exponentially-weighted Mean

I wrote a simple function in Python to calculate the exponentially weighted mean: ...
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0answers
79 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 ...
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0answers
46 views

Holt Winters Initialization Issue

I am using an additive seasonal Holt-Winters model to compute confidence band of my data. I followed the HW initialization process described by Rob J Hyn­d­man. The confidence band is derived by ...
0
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1answer
110 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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2answers
214 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 ...
0
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1answer
131 views

How to dampen forecast to improve accuracy?

According to Armstrong there is ample empirical evidence that dampening trends in uncertain and complex long term forecasting helps improve accuracy/reduce forecasting errors. What I'm not able to ...
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1answer
344 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 ...
1
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1answer
225 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 ...
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0answers
77 views

Why multiplicative Holt-Winters requires strictly positive data points?

I've seen that multiplicative Holt-Winters requires strictly positive data points. I was wondering why it does not allow zero values?
2
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0answers
68 views

How to select the exponential decay constant for weighting in proc logistic?

I am trying to predict the sales conversion using proc logistics in SAS. Right now I have around 3 months of data, and it will gradually grow to more than an year over time. My intuition is that the ...
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0answers
60 views

smoothing nodes values on a graph given adjacency matrix

I am currently looking for a method to smooth values on a graph (composed of vertices and edges). For example I have a graph with a set of nodes V and I want to be able to smooth it. I could have ...
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0answers
146 views

Improving Python Exponential smoothing

I am going to improve my code to the Exponential smoothing I submitted to Statsmodel which can be found here. The code handles 15 different variation Standard Exponential Smoothing models including ...
0
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1answer
119 views

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?
2
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2answers
306 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) ...
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0answers
95 views

Which method of implementing the Brown's linear exponential smoothing is correct?

I am trying figure out what is the difference between Brown's linear model for double exponential smoothing and Holt's model. So the differences can be implemented into a Holt model using if ...
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2answers
550 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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1answer
424 views

What is the minimum historical data/sample data required for a time series forecasting analysis?

Are there any statistical power analysis/sample size deteminations methods for time series data analysis/forecasting? For example if I have time series of 30 data points, how can I with confidence ...
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1answer
1k views

Holt's Linear and Holt-Winters in R

With the below code, I have run Holt's linear and Holt-Winters forecasts using Excel / Solver. I wanted to replicate this using R (Excel can be a pain) but I am getting the below error with ...
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3answers
261 views

Using simpler models in place of more generalized and complex models

I was reading about BATS (Box-Cox transformation, ARMA errors, Trend and Seasonality) and TBATS (Trigonometric, Box-Cox transformation, ARMA errors, Trend and Seasonality) models. I was wondering ...
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1answer
549 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
239 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. ...
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218 views

Multivariate EWMA

Is there any package in R which computes the Multivariate EWMA? I have a data frame of 4 series and I do not want to use a simple rectangular method to compute the covariance estimator. So is there ...
2
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1answer
1k 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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0answers
255 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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1answer
133 views

Seasonal exponential smoothing without trend

Why multiplicative property exists only for the exponential smoothing with seasonality and trend (Winter's additive and Winter's multiplicative models) and not for the exponential smoothing with only ...
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1answer
441 views

Multivariate exponential smoothing and Kalman filter equivalence

Suppose the time-series $X$ is hidden state Gaussian random walk and we observe $Y = X + e$, where $e$ is gaussian white noise independent of $X$. The Kalman estimator of $X$ in this case has a ...
2
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2answers
1k 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, ...
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3answers
573 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, ...
1
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1answer
360 views

Do you think smoothing constant value, alpha, in SES method is a control parameter or process parameter?

There is a debate in selecting the smoothign constant in Single Exponentioan Smoothing method by practitioner or considering it as a process parameter? Could you please provide your opinion regarding ...
1
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1answer
227 views

use Exponential smoothing to forecast lead-time demand

I'd like to use Simple Exponential smoothing to forecast the lead-time demand for inventory control, I have monthly data and LT+1 is equal to 5 months, can I do a forecast using SES which gives me a ...
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2answers
563 views

Holt-Winters and importance of R-square

Is R-square an important measure in Holt-Winters method?
0
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1answer
267 views

Values of $\alpha$, $\beta$ and $\gamma$ in ets in forecast package

I am using the forecast package in R. I wanted to know how the ets() function finds the value of $\alpha$, $\beta$ and $\gamma$? ...
3
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2answers
657 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 ...
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2answers
3k views

Value of alpha and beta in Holt's exponential smoothing method

How to choose the best values of alpha and beta in Holt's exponential smoothing? Leaving it upon R gives me $\alpha$ =1. Is this appropriate? Entering different values of alpha and then comparing ...
4
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3answers
5k 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 ...
2
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2answers
339 views

Smoothing constant in single exponential smoothing

I have some SKUs and I'd like to do a forecast using single exponential smoothing as a forecasting method, when should we go for small value of alpha (.05,.1,...) and when for bigger ...
2
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3answers
385 views

Regression with exponentially-smoothed errors

I'm just starting to look into exponential smoothing models. Is there a way to fit a linear regression with exponentially-smoothed errors, similar to the standard technique of fitting a regression ...
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0answers
254 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) ...
0
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1answer
303 views

Why doesn't the exponential smoothing forecast package in R provide confidence intervals for the fitted values?

The upper and lower prediction intervals for the forecast periods are provided by the forecast() function. However, neither prediction or confidence intervals seem to be available for the fitted ...
0
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2answers
1k views

How to pick coefficients for Holt Winters?

I'm using Holt Winters to predict sales revenue from past performance. Seasonality and changing trends exist in the data. One of the reasons chosen for Holt Winters is that it is fairly simple ...