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

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27 views

Holt-Winters for Imputation

I have found Holt-Winters seasonal method a very decent method for forecast, specifically for cases where more recent observations are more representative of the near future. The method equally sounds ...
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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 ...
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1answer
272 views

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, ...
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1answer
263 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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1answer
50 views

simple exponential smoothing - Ljung-Box test - residual

While reading this page on time series (http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/src/timeseries.html), I found this sentence: The Ljung-Box test showed that there is ...
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1answer
52 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 ...
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1answer
421 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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0answers
32 views

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 ...
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0answers
471 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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0answers
222 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 ...
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0answers
12 views

'Level' still seems periodic after Season Decomposition

I've used tbats for this transformation: Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components My (...
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0answers
159 views

R: Calculating prediction intervals (95%, seasonal naive and holt winters)

Could somebody explain to me the theory behind how R calculates the 95% prediction intervals for my 12 step ahead forecasts in (1) a seasonal naive model and (2) a Holt-Winters forecast. My code is ...
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0answers
231 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) ...
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0answers
166 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
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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 ...
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0answers
111 views

pandas.ewma to be used to make prediction

I would like to implement EWMA to be able to make prediction based on historical data. I am using EWMA in pandas. After playing with com and span, it seems like predictions are not based on ...
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0answers
44 views

Does “level” in exponential smoothing stand for the “mean”?

In triple exponential smoothing it is said that there are estimates for 3 components: level, trend and seasonal. Does "level" here stand for "mean"? In single exponential smoothing is only the level ...
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0answers
68 views

How come Exponential Smoothing without trend producing astonishing results when there is trend in the time series

I have a time series and a plot of it is presented below for consideration. A linear trend was identified in the series both visually and using statistical tests such as Cox-Stuart and ManKendall. ...
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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 ...
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0answers
94 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
313 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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0answers
370 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 ...
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0answers
18 views

Sales forecasting: Unsure about data grouping

I am trying to implement a simple, short-term (1-4 weeks) forecast of product revenue/sales. The data I have is brand category product revenue where ...
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0answers
16 views

Detect increase/decrease events on time series

Given a time series, I have to detect two types of events: 1) "medium" decrease 2) "high" increase Event detection should be "fast enough". I used quotation marks as I'd like to set different ...
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0answers
8 views

Linear regression (best fit line) on moving averages vs raw data?

I have a series of sets of data over a period of time, with the amount of data available being quite variable between sets. One has points for almost every day but is really quite noisy; another has ...
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59 views

Time Series ETS model out-of-sample one-step-ahead forecasts. Weird Results

EDIT Secondary Question: Does using one-step ahead predictions even make sense, logically, for anomaly detection? I tried introducing anomalies manually and it seems the one-step-ahead timeseries ...
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13 views

Forecasting time series one step ahead - with and without taking into account trend

In the Exponential Smoothing chapter of Hyndman and Athana­sopou­los's online book 'Forecasting: principles and practice', the authors first introduce simple exponential smoothing and then Holt's ...
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4 views

Leadtime Analysis

I need to know which statistical method to use to analyze past leadtime data. My goal is to find a more "realistic" leadtime than plugging in an arbitrary number, such as 18 weeks. The data I am ...
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43 views

Understand Exponential Moving Averages in Matlab

I'm unable to manually replicate the exponential moving average values that I see when using MATLAB's tsmovavg function. There seems to be some ambiguity online ...
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0answers
20 views

Upper and lower limits for ets()

In the following function ets(x, lower=c(rep(0.0001,3), 0.8), upper=c(rep(0.9999,3),0.98)) How does one interpret the upper and lower limits for the ...
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40 views

How to find out and quantify rate of change of trend in time series?

I have a temperature data which has approximately exponential trend how can I find the temperature at which temperature is approximately constant. Is there any way to quantify the same?
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14 views

How to calculate initial states in ets function when we refit model to new data set?

usfit<-ets(usnetelec[1:45],model="AAN") test<-ets(usnetelec[46:55],model=usfit) s1 <- usfit$states[45,] s2 <- test$states[1,] How can we calculate ...
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134 views

measuring accuracy in one step forecast(using auto.arima() and ets() in R

I’m working on workers’ remittances data (quarterly) for Bangladesh. The data span is from 1980 quarter 1 to 2014 quarter 4. My objective is to do univariate time series forecasting with ...
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84 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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28 views

Which time series model to use?

Hi I have a large data set of objects, each containing a list of the same attributes. The data is arranged in a time series so that the value for an attribute for an object is indexed by its time. ...
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0answers
88 views

EWMA or Moving Average when Estimating Trend in Seasonal Data

What is generally the best practice when estimating trend (non-seasonal component) in seasonal data? Centred Moving Average as suggested by MatLab docs Averaged EWMA (backwards & forwards) as ...
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0answers
400 views

Holt-Winters Method & Triple Exponential Smoothing

what the different about HW method & triple exponential smoothing? Some people say it same. but I still confused about the formula, its look the different.. Please help me, I need for my first ...
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0answers
152 views

“Future-independent” smoothing methods (as exponential smoothing)

I'm searching for time series smoothing algorithms, which give "future-independent" results - each next smoothed value depends only on previous data (smoothed or not smoothed), but not on any future ...
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130 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 ...
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0answers
72 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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109 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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235 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?
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515 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 ...
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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) ...