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

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53 views

Fitting a nonlinear regression $Y=1 - a^{-bx}$

I have the following dataset: where X:Y 1:0.81 2:0.86 4:0.9 6:0.93 8:0.96 10:0.98 12:0.99 14:0.99 16:1 18:1 20:1 ..:1 Since the limit of the regression ...
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7 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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9 views

How to define holt winters model for forecasting using output R [on hold]

My research is comparing between SARIMA & HoltWinters multiplicative. I got confused when I tried to define forecasting model for HoltWinters multiplicative, because I thought model SARIMA and ...
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9 views

Refitting model Holt winters with Testing Data in R [closed]

I feel confused to refitting model Holt Winters with my Testing Data in R. Here's my model from my Training Data Is it okay using this method below to refitting the model with my Testing Data? ...
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1answer
15 views

Using Holt-Winters formula, how do you choose which seasonality to begin your first forecast period with?

This is probably a pretty basic question but I'd like to understand how you choose a seasonality number for the first forecast period in a Holt-Winters model. If you need to forecast 8 months ahead ...
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45 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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10 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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2answers
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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9 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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3 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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25 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
13 views

Usage of AIC for comparing models [duplicate]

Can AIC be used to compare a model with exponential smoothing with linear regressions?
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1answer
216 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
32 views

how to compare ARIMA and exponential smooting model numerically

The exponential smoothing method gives us values like SSE and $R^2$ for the entire model. The ARIMA model, however, does not give us these values. So, given the same data, how do one decide which ...
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2answers
360 views

Problem with proof - why exponentially smoothed time series is biased

I'm working through the proof why the exponential smoothing is a biased estimator of a linear trend. The book is trying to describe the expected value of an exponentially smoothed time series. It's ...
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1answer
50 views

Why do my weights have to equal one?

I'm currently learning the very basics of exponential smoothing. As follows: The book first presents the following model: $$\sum{\theta^tY_{T-1}}$$ It then claims that the sum of all weights add ...
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1answer
193 views

How to choose automatically between Auto.ARIMA, ETS and STL in R

I'm working on a sales forecasting package which should be easy to use for the end user. Given a time series with historical sales data I would like to automatically select one of the three forecasts: ...
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1answer
28 views

Exponential Regression with x outside of exponential

I am trying to do exponential regression by matrix notation, and I am trying to figure out to create my $\mathbf{X}$ matrix to fit my model. I know that I need to use a model function of the form $c_1 ...
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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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98 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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1answer
70 views

Efficient automated prediction for a 1000 growing, big data sets. How to?

I have daily data points of the number of sales, but I am not looking at historic data only. My system delivers a new data point every day and in the evening I want to predict the number of sales ...
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27 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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43 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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1answer
46 views

How can I calculate the PI of (simple) exponential smoothing?

I would like to calculate the prediction intervals of exponential smoothing. In R there is a function (ses in a forecast package) which calculates the point forecast and also the prediction intervals. ...
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153 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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127 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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79 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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1answer
106 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 ...
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206 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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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
99 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 ...
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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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80 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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1answer
136 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 ...
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1answer
485 views

time series forecasting using auto.arima and exponential smoothing

I am working with workers’ remittance quarterly data for Bangladesh. Here I am doing time series forecasting using R. I am applying auto.arima model and exponential smoothing model. I want to compare ...
3
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1answer
118 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 ...
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50 views

Exponential Smoothing with Causal Regressors

I am trying to develop several approaches to analyze the effect of covariates on retail sales . the first approach i am trying to use is exponential smoothing with regressors (for its simplicity to ...
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67 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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5answers
406 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?
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1answer
209 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
153 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 ...
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1answer
78 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 ...
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3answers
2k 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. ...
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2answers
190 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: ...
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2answers
2k 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 ...
0
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1answer
51 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
49 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 ...
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1answer
42 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 ...
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389 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 ...