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

learn more… | top users | synonyms

3
votes
1answer
140 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 ...
1
vote
0answers
37 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 ...
1
vote
1answer
2k 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
votes
1answer
1k 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 ...
0
votes
0answers
122 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
votes
1answer
239 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 ...
3
votes
2answers
150 views

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 ...
0
votes
0answers
67 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
votes
0answers
160 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). ...
0
votes
0answers
103 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 ...
2
votes
1answer
2k 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: ...
5
votes
1answer
595 views

Standard Deviation of an Exponentially-weighted Mean

I wrote a simple function in Python to calculate the exponentially weighted mean: ...
1
vote
1answer
254 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 ...
0
votes
1answer
391 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, ...
4
votes
2answers
1k 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
votes
1answer
532 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 ...
3
votes
1answer
2k 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
vote
1answer
1k 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 ...
1
vote
1answer
71 views

Strange results in Holt forecast

I am trying to understand what could be causing these strange values to appear on applying a Holt model to a vector. The data represents actual sales of an item. ...
0
votes
0answers
224 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?
4
votes
1answer
1k 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 ...
2
votes
0answers
116 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 ...
1
vote
0answers
93 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 ...
0
votes
0answers
503 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
votes
1answer
231 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
votes
2answers
649 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) ...
1
vote
0answers
299 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 ...
2
votes
3answers
2k 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 ...
1
vote
1answer
1k 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 ...
1
vote
1answer
3k 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 ...
1
vote
3answers
381 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 ...
2
votes
1answer
1k 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
votes
1answer
422 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. ...
1
vote
0answers
363 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 ...
3
votes
1answer
4k 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
votes
0answers
460 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 ...
1
vote
1answer
256 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 ...
1
vote
1answer
631 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 ...
4
votes
2answers
2k 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, ...
8
votes
3answers
1k 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
vote
1answer
549 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
vote
1answer
325 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 ...
0
votes
2answers
882 views

Holt-Winters and importance of R-square

Is R-square an important measure in Holt-Winters method?
0
votes
1answer
455 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
votes
2answers
1k 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 ...
1
vote
2answers
5k 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
votes
3answers
8k 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
votes
2answers
525 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
votes
3answers
527 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 ...
0
votes
0answers
287 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) ...