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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138 views

Holt-Winters: Can I use more than one seasonal cycle for SSE minimisation?

I am minimising SSE to estimate the parameters and starting values for a Holt-Winters model. I.e. "forecasting" the values using different parameters, measuring the sum of squared errors of these "...
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701 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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235 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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415 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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3answers
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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 values(.8,.9,...)?...
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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: ...
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1answer
3k 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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1answer
2k views

Holt Winters with exogenous regressors in R

I need to forecast using HoltWinters with regression parameters using R. But I found there is not any option of xreg in ...
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1answer
4k 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
293 views

What exactly is the exponential smoothing model?

I see the term "exponential smoothing" model used a lot in different applications but I never understood what exactly it is. Is it just a MA(1) model? Or is it any moving average model, meaning it ...
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1answer
2k views

Holt-Winters prediction intervals

I noticed that the Holt-Winters function in the "forecast" package in R contains prediction intervals. This was interesting, as it is not intuitively obvious to me how prediction intervals could be ...
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1answer
106 views

Does an exponential smoothing model have roots the way ARIMA models do?

I read elsewhere in this forum a comment (which I have since been unable to find again) about Exponential Smoothing models not having unit roots. I (sort of) know how to figure out the roots of an ...
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537 views

ARIMA on top of exponential smoothing for forecasting

I have time series data on temperature, both hourly and daily. I want to forecast the time series. Is it possible to combine ARIMA model and Exponential Smoothing methods to achieve the goal? Would ...
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2k 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?
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1answer
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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 ...
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1answer
1k 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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1answer
27 views

General exponential smoothing to linear functions of past observations

I am just trying to derive an equation in "Forecasting with Exponential Smoothing" page 36 section 3.2. I am given the following $\hat{y}_{t|t-1} = \textbf{w}'x_{t-1}$ $\epsilon_{t} = y_t - \hat{y}...
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267 views

Shifted fitted data in Exponential Smoothing, how to solve?

I've a doubt in the application of the exponential smoothing for pure forecasts. I'm using this type of model in these days, for the automatization of some algorithms. This time i'm working on non-...
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1answer
2k 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
9k 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
711 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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1answer
34 views

time series forecasting - predicting the next 24 hours

I have much the same problem as predict-the-next-24-hours, I have several years of hourly data of demand, and I would like to predict the next 24 hours. Ignoring the multi-seasonality issues - is it ...
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3answers
468 views

Negative Forecast using Holt-Winters

I tried to use Holt-Winters for forecasting, but it gives me negative values, but since these are demand quantities they cannot be negative. ...
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350 views

Positive smoothing with the fda-package (Functional data analysis)

In the book Functional Data Analysis with R (Ramsay&Silverman) there is described the possibility to do the "positive smoothing" if it’s needed instead of the "normal smoothing". In the books ...
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82 views

What is a recommended forecasting method for predicting air passenger numbers?

I am doing a forecasting project for school and trying to predict air passenger numbers based on 18 months of historical data from the airport. I have considered applying Holt-Winters seasonal ...
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1answer
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Deciding inital values of trend, season and level for Holt winter's seasonal additive smoothing

I am following this for understanding Holt winter's seasonal additive smoothing. I am not able to find any explanation for deciding initial values for trend, level and season for seasonal additive ...
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1answer
2k views

Seasonal decomposition or Holt-Winters methods for forecasting?

When you have a time series that contains both trend and seasonal components, I learned that either seasonal decomposition (e.g., forecast the deseasonalized series, then add back the seasonal factor ...
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1answer
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Holt-Winters parameters in R

I'm trying to replicate some values from a holt winters calculation made in excel by someone else. I have the time series time_x, and I'm using the forecast package. The problem is when I run the ...
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1answer
2k 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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36 views

Exponential forecasting with non-constant variance

I want to use exponential forecasting to detect outliers, but my data are means of samples of different sizes. The series was formed by taking the average, every five minutes, of measurements ...
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30 views

Time series when the data are averages of different sample sizes

I am trying to analyse a collection of time series where the observations are averages of different sample sizes. I'm looking at measurements from a high volume system with many users.I get averages ...
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278 views

Is there any interpretation of parameters in Holt Winters method?

I am doing forecast on time series on R and I use exponential smoothing method Holt Winters. Does a value of $\alpha$ close to $0$ or $1$ "mean" something particular about the series? Same question ...
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266 views

How much do the parameters in the Holt-Winters model matter?

When fitting a Holt-Winters model, I usually take the approach of retrospectively "predicting" some known historical values for the series, and optimising the coefficients for the parameters by ...
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490 views

Alternatives to Holt-Winters models when the seasonality pattern has changed

I am forecasting a series of daily volumes in terms of units processed for a particular time period (the period around Christmas). Historically, I have used a Holt-Winters model, with the minor ...
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254 views

Adjust decay rate dynamically

Say I have a stream of values $\langle s_1, s_2,\ldots\rangle$ coming in and a function $$E_{s_1:s_n}(t) = E_{s_1:s_{n-1}}(t-1) + \alpha\cdot (s_t-E_{s_1:s_{n-1}}(t-1))$$ that compute their ...
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Does it make sense to think about steady state forecast error for Kalman filter with time-varying parameters?

The environment: We have a state equation: $$ \xi_t =F\xi_{t-1} + v_t $$ and a measurement equation $$ y_t = H\xi_t + w_t $$ with $$ E\Bigg[\begin{pmatrix}v_t\\w_t\end{pmatrix}\begin{pmatrix}v_t'&...
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3answers
509 views

Can simple exponential forecasting be used for a non stationary series?

I have a non stationary series with trend and seasonal components. I want to use simple exponential smoothing ONLY for forecasting. Does the series need to converted to stationary before using SES? If ...
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'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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827 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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990 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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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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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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843 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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How to derive the variance of a weighted moving average?

I have a problem understanding a piece of a paper. Greatly appreciate any hint or help. It says: A sensor records $Z(i)$ at intervals of 1 second and calculates background values $U(i)$ using ...
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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 ...
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3answers
693 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
1k 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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574 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 ...
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1answer
2k views

Is it OK to use Holt-Winters to predict longer-term future sales?

I have a full year of 2017 daily sales data and am looking forward to predicting the daily sales for next month. It has strong seasonality of 7, so what I did is to use Holt-Winters to calculate the ...
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1answer
1k 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 ...