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

learn more… | top users | synonyms

0
votes
0answers
18 views

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

Premise: I am using the stlm() and ets() exponential smoothing methods in the R forecast package to create forecasts of a time-series. I am creating a model with my training data then want to ...
2
votes
0answers
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 ...
0
votes
2answers
21 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 ...
0
votes
0answers
8 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 ...
0
votes
0answers
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 ...
0
votes
0answers
17 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 ...
0
votes
0answers
13 views

Usage of AIC for comparing models [duplicate]

Can AIC be used to compare a model with exponential smoothing with linear regressions?
1
vote
1answer
141 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, ...
1
vote
1answer
30 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 ...
7
votes
2answers
358 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 ...
0
votes
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 ...
0
votes
1answer
159 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: ...
1
vote
1answer
26 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 ...
0
votes
0answers
19 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 ...
1
vote
0answers
81 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 ...
0
votes
1answer
66 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 ...
0
votes
0answers
25 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?
0
votes
0answers
13 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 ...
1
vote
0answers
40 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 ...
0
votes
1answer
45 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. ...
2
votes
0answers
139 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 ...
0
votes
0answers
113 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 ...
0
votes
0answers
76 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) ...
3
votes
1answer
105 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 ...
1
vote
0answers
174 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) ...
0
votes
1answer
49 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 ...
1
vote
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 ...
0
votes
0answers
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. ...
0
votes
0answers
73 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 ...
1
vote
1answer
123 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 ...
0
votes
1answer
422 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
votes
1answer
113 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 ...
0
votes
0answers
49 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 ...
1
vote
0answers
64 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. ...
0
votes
0answers
54 views

Confidence interval for exponential moving average and variance

There are well known formulas for the exponential moving average and variance. Just for the completeness of the question, for each new x in a series of X(1..n) online EMA and EMVar can be estimated as ...
3
votes
5answers
403 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?
2
votes
1answer
190 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
141 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 ...
1
vote
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 ...
9
votes
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. ...
2
votes
2answers
181 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: ...
1
vote
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
votes
1answer
50 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 ...
1
vote
1answer
47 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
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 ...
0
votes
0answers
367 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 ...
0
votes
0answers
143 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 ...
3
votes
1answer
133 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
35 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 ...