Forecasting involves estimating the value or distribution of a random variable which has not yet been observed.

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Forecast done by Holt's winter method has seasonality in error (Auto correlation graph) [on hold]

I am doing forecasting for six month daily data for item sales of which increases on friday and saturday. I am using Holts Winters method and have done the forecasting getting Thiel's U Statistics ...
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96 views

Explaination of what Nate Silver said about loess

In a question I asked recently, I was told that it was a big "no-no" to extrapolate with loess. But, in Nate Silver's most recent article on FiveThirtyEight.com he discussed using loess for making ...
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7 views

Root causes of error in a forecast consisting of two multiplicative factors

I have a warehouse that packages units and ships them. Any number of units can go into the same package, including only 1 unit. I have a forecast for number of units and units per package (UPP). From ...
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How to assume data in 'lesser intervals' of a parameter having its genuinely measured data on regular large intervals?

I need to analyze a 12 year long performance data of a waste water treatment plant in Sydney . The data has 250 parameters. As a part of schedule sampling, some of the parameters are measured 3 times ...
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11 views

Double exponential smoothing alternative?

I am testing double EWMA smoothing on a time series of financial data to attempt to forecast the next point, xt+1 at time t. The original method I used (from wikipedia) is below: for t = 1 : s1 = x1 ...
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Forecasting seasonal components in X-13ARIMA-SEATS

Forecasting seasonal components is an important practical problem in finance, where products that are highly exposed to monthly seasonality in consumer prices are traded. For example, one can trade ...
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6 views

Extracting X-13ARIMA forecasts of seasonal effects [on hold]

I am attempting to forecast seasonal effects in various consumer price index components (foods, services, goods, etc.). In other words, I am interested in obtaining - for each time series - forecasts ...
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23 views

Diebold Mariano test (in R)

As I asked in my answer to this question: does anyone know if the DM test (in R in this case) is supposed to be made with h=h-1? If not, am I supposed to make several prediction sets (with h ...
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25 views

How to predict the risk of an event?

I'm working on a medical problem, where I want to analyze the effect of taking cholesterol medications on the occurrence of heart attack. Once a medication with a specific dosage is prescribed, it'll ...
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11 views

Information on NN GC1 Forecasting Competition

I am looking for publications or other information on the results of the NN GC1 time series forecasting competition (http://www.neural-forecasting-competition.com/index.htm). The website provides ...
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1answer
55 views

When using a limited data set, how can I use excel to forecast future values?

To preface, I am a statistics novice, but I am faced with a problem that I cannot seem to be able to satisfactorily resolve. The problem is as follows: I am working to forecast future sales for one ...
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15 views

Making a forecast: Confidence/Prediction/Tolerance Interval?

I understand the the difference between these three types of intervals but I will summarize briefly: Confidence Interval: an interval that will contain the true mean value say, 95%, of the time. ...
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24 views

Regression or time series model to predict trend

DATA I have the following data at hand: data about internet usage, per hour, per user, per part of the day (morning, afternoon, evening); the category of websites visited and their duration; ...
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25 views

Why does the Arima() method in the forecast package in R not calculate standard errors for coefficients passed to 'fixed'?

In the Arima() method, in the forecast package in R, I can provide a vector of parameters to the ...
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2answers
65 views

Method for quantifying intervention effect in time series

How can the magnitude of an intervention be quantified in a segmented time series regression? I am attempting to replicate the methodology of Decline in pneumonia admissions after routine childhood ...
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1answer
18 views

How to extrapolate this simple trend line into the future for the purpose of forecasting in Matlab?

We have the following data points in variable data pertaining to a problem that we are solving: ...
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9 views

How to fit a forecasting model on this irregular time series in Matlab to obtain predictions? [closed]

We have some data values from the past (1214415 to be exact over 1 minute intervals). We are only interested in the 'peaks', that is, how the trend pertaining to the maximum is increasing with time. ...
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1answer
30 views

VAR model: good diagnostics but poor forecasting performance

I constructed a VAR model of order 4 where some of the variables are statistically insignificant. The model is based right in terms of diagnostics (no autocorrelation of residuals, normal distribution,...
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Estimation and forecasting ARMA: differences between Matlab and Stata

I have to forecast values from an AR(1) model. My sample is composed of 192 observations. I estimate my model with the 182 first observations and forecast the 10 last observations. I have done this ...
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1answer
35 views

How to forecast from VECM (in R)?

I am interested in forecasting with a vector error correction model (VECM). I am facing a problem of not being able to transform a cointegrated series into a VECM model using the stationary series. ...
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1answer
30 views

Forecasting ARIMA with `predict` vs `forecast` in R [closed]

Data consisting of 30 values is stored in a time series time. After applying ARIMA modelling on time, I used ...
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19 views

Techniques to forecast demand from a transaction log

Suppose we have a log file of transactions. Which, have at least the variables: Customer, Product, ...
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30 views

What is the difference between ARMA+Fourier and TBATS model?

I am just wondering that, in terms of the multi-seasonal time series forecast, what is the difference between using auto.arima find the ARMA order, then fit <...
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1answer
21 views

Interpreting BATS model information using forecast package in R

I have a forecast object in R. When I look at the summary I can see 'Model Information: BATS(1, {1,1}, -, -)' What do these numbers in the parentheses stand for?
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10 views

How to convert hourly data into a time seris in R [migrated]

I have hourly data arranged by date and the dput is given below: ...
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16 views

How to make shrinked forecast for the extreme value?

Let me use made-up example: John loves running. He decided to run in his local half-marathon for the first time in his life. He never measured exactly how fast he runs the distance, but while ...
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49 views

How does a LOESS model do its prediction?

I understand the theory behind LOESS, but how does it do prediction without coefficients? I'd like to use LOESS prediction, but need to be able to explain it.
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52 views

Predict from estimated ARIMA model with new data

Suppose I have a training dataset, I use auto.arima (from "forecast" package in R) to fit the training data. As a result I get the lag and integration orders $(p, d,...
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23 views

How to extend the separated trend line to predict future time series values in R?

We have data from border router devices that depict the bits per second from the past 4 years. There are some missing values or values too low when backup devices were in use. Every day has a BPS ...
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What is the SARIMA (2,1,0)(0,0,1)_12 euqation? [duplicate]

I have problems to find the euqation for Arima (2,1,0)(0,0,1)12....would be nice to get some help!
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26 views

Booking Pickup reservation problem

I am solving a reservation forecasting problem, where I need to predict what will be the reservations at a given point (say 31 Dec 2016) and also how will it pick up in 60 days prior to the given date....
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2answers
52 views

Modelling moving holiday effects in forecasting

I have researched multiple related questions(here, here) but it lacks detailed context and solutions. My goal is to improve my daily sales forecast accuracy after having incorporated a simple holiday ...
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1answer
56 views

Time series prediction using ARIMA vs LSTM

The problem that I am dealing with is predicting time series values. I am looking at one time series at a time and based on for example 15% of the input data, I would like to predict its future values....
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75 views

Forecasting: residuals from seasonal decomposition appears to be highly auto-corelated, why?

I am using a publicly available data Kaggle: Rossmann Store Sales and trying to forecast sales. I am using Python. My timeseries is stationary, confirmed via the Dickey-Fuller test. However, I wanted ...
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Confidence interval of fitted value and forecasted value form tbats model in forecast package in R

I have half hourly multi-seasonal(daily, weekly, quarterly, yearly) time series data and I divided them into training part and testing part. ...
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Plotting Just the Seasonal Component of ETS Model - R [migrated]

This is probably a simple question but my R skills are still in the learning stages. I am trying to get just a plot of the seasonal component in an ETS time series model and I also would like the x ...
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52 views

Time series prediction in R over more than 180,000 past data points takes forever?

We have data values pertaining to BPS (bits per second) traffic on a networking device. We have data from for a particular month (October) from the past 4 years. The data points are available in a 1 ...
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38 views

Forecasting multivariate time series data stream

I have a multivariate time series data stream. I am looking for a method that can forecast the next value of one of the variables as the data comes in. (It would be a major advantage if there's an R ...
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90 views

Identifying lagged effects / Distributed Lag Model

I would like to create a linear distributed lag model in order to do some forecast and also being able to interpret the results. Unfortunately I'm a bit confused with the process I should follow....
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35 views

Is forecasting and predictions part of Inferential or Descriptive?

Can someone please explain to me which statistics forecasting and predictions are part of? Inferential or Descriptive? I am working on an homework. I was unable to come across the answer in my reading....
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31 views

I got a 0.1% improved MSFE result by my own estimator, is this worthwhile to be published? [closed]

As the title, recently I developed some nonparametric forecasting method which slightly modified the previous method. Then, I could about 0.1% improved result comparing to the previous method. But I ...
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46 views

Does combining forecast models produce good prediction intervals?

In this blog post, @rob-hyndman says: If you only want point forecasts, that is the best approach available in the forecast package. It is also better than any of the commercial software (at least ...
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How to know that your machine learning problem is hopeless?

Imagine a standard machine-learning scenario: You are confronted with a large multivariate dataset and you have a pretty blurry understanding of it. What you need to do is to make predictions ...
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37 views

Short time series forecast [duplicate]

We have a series of monthly data for 20 months (it is not possible to obtain more data). These are the number of medical consultations encoded in a public hospital and we only have monthly data for ...
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383 views

When have I to stop looking for a model?

I'm looking for a model between stockprices of energy and the weather. I have the price of the MWatt bought between the countries of Europe, and a lot of values on the weather (Grib files). Each hours ...
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30 views

Optimize unknown time series model

I have the MAPE figures of a time series model with multiple parameters for different lags. I can simulate values for the multiple parameters and can get the MAPE values. The problem is that the ...
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1answer
54 views

Should I adjust a Time Series dataset using X-13ARIMA-SEATS before running forecasts algorithms?

This question is sort of a follow up of this great thread. I have a Time Series Analysis project in which I have to create a model to predict new values given historical univariate data using R. My ...
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41 views

Time series model to forecast electricity demand given temperature and electricity price

I currently have half-hourly electricity demand, half-hourly electricity price and hourly temperature from 2012 to 2016, and I would like to do both short-term and long-term forecast of electricity ...
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1answer
53 views

Are log difference time series models better than growth rates?

Often I see authors estimate a "log difference" model, e.g. $\log (y_t)-\log(y_{t-1}) = \log(y_t/y_{t-1}) = \alpha + \beta x_t$ I agree this is appropriate to relate $x_t$ to a percentage change in $...
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Forecast (R) with Trend, Seasonality and Promotions (Causals)

I have aggregated sales data along with price discount at month level for two years. There are seasonality, trend and also causals - the impact of price promotions (discount, in percentage). I want to ...