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

learn more… | top users | synonyms

6
votes
3answers
6k 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 ...
6
votes
3answers
260 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. ...
6
votes
3answers
931 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, ...
4
votes
2answers
532 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 ...
4
votes
3answers
7k 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 ...
4
votes
1answer
263 views

Standard Deviation of an Exponentially-weighted Mean

I wrote a simple function in Python to calculate the exponentially weighted mean: ...
4
votes
1answer
808 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 ...
3
votes
5answers
349 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?
3
votes
2answers
113 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 ...
3
votes
2answers
894 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 ...
3
votes
1answer
56 views

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

Ive 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 ...
3
votes
1answer
80 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
votes
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, ...
3
votes
1answer
63 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
votes
1answer
351 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
votes
0answers
334 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 ...
2
votes
2answers
407 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
2answers
110 views

Why do I get linear model when I tried to fit exponential model?

I was wondering why do I get linear model when I'm using exponential model, y = a * exp(-b*-x), to fit my data. Here is my code: ...
2
votes
1answer
68 views

Forecasting with two or more causal factors using the Holt-Winters method (in R)

Is there something similar to the Holt-Winters forecasting method in R, which can be used to model two or more explanatory factors?
2
votes
1answer
47 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 ...
2
votes
1answer
988 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: ...
2
votes
2answers
407 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) ...
2
votes
1answer
2k 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 ...
2
votes
3answers
453 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 ...
2
votes
0answers
100 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). ...
2
votes
1answer
996 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 ...
2
votes
0answers
97 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 ...
2
votes
0answers
195 views

Exponential moving average with sub-interval relevance / varying timeframe

I need to calculate an exponential moving average for a series of data. The intended sampling interval is fixed (say 1s) but the data stream has varying intervals (data intervals vary from 0.01s to ...
1
vote
2answers
4k 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 ...
1
vote
3answers
311 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 ...
1
vote
1answer
181 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
2answers
382 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 ...
1
vote
1answer
960 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 ...
1
vote
2answers
472 views

Single exponential smoothing

I think my question is quite simple and stupid: What do we forecast using single exponential smoothing model: the next value of the observed time series or the next value of the level which lies in ...
1
vote
1answer
35 views

Smoothing intraday data when only looking at a certain time range

I have an intraday price series (5 minute) over several months. I want to smooth the data using an ema but also i am only interested in analysing the series between certain time periods eg between 8am ...
1
vote
1answer
44 views

Exponential smoothing state space model - stationary required?

I came across with the Exponential smoothing state space model for time series forecasting. My question is if it does require that the time series is stationary? Is there any paper that explicitly ...
1
vote
1answer
36 views

Explain double and triple smoothing methods in plain english

As above, anyone willing to take out the mathematical jargon and notations - i can get that from any book on time series and explain what really is happening, why and how? Surely, there is someone who ...
1
vote
1answer
792 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 ...
1
vote
1answer
504 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
66 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. ...
1
vote
3answers
1k 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
2k 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
1answer
491 views

Standard error and p-values of exponential smoothing weights

Is there any justfification for producing a standard error of a single exponentially weighted coefficient? If yes, how can we interpret the p-value? Background I use SAS ETS to estimate a single ...
1
vote
1answer
72 views

Analyzing seasonality in data

In order to analyze the data in presence of seasonality, I used two methods: Proportional hazard model (Cox model) and time series method (Triple Exponential Smoothing (Holt Winters Method)). Now , my ...
1
vote
1answer
772 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
546 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 ...
1
vote
1answer
450 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
280 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 ...
1
vote
0answers
40 views

Constant in arima model whether to include or exclude?

I have a very basic question on including constant in Arima models. I'll illustrate this by an example. I have the following ACF and PACF of a weekly time series that is differenced at lag 1 (trend) ...
1
vote
1answer
53 views

How can a 95% confidence interval not overlap with my trendline forecast?

I used holt winters in excel to forecast 12 moths ahead based on 40 months of historic data. Then I ran a monte carlo simulation to create 1000 scenarios and computed upper and lower bounds to create ...