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

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what is the best forecast interval for tbats?

I used tbats to fit a model to a set of weekly data (but only for weekdays) so I have seasonality of 5 for daily and 261 of annual. I wonder if tbats works better by updating the model using observed ...
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9 views

Parameter estimation for dynamic regression models with correlated noise ARMA errors

I'm reading the Dynamic Regression Models chapter ( https://www.otexts.org/fpp/9/1 ) in Professor Hyndman's book, and I couldn't understand how to fit the regression model when the error is modeled ...
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2answers
33 views

Why is the intersect negative and what does my regression show

I am trying to get my regression right. I want to see, if subs increase how much increase in revenue is seen. The dependent variable is Revenue while the independent variable is subscribers. Least ...
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10 views

updating a forecasting model including the new observed data with the historical data

I want to have a one week ahead forecast for my data which includes a four years of daily historic data (three years are used as train set and the 4th year is used as the test set). I can use three ...
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11 views

Call Center Arrival Forecasting [on hold]

Can anyone suggest me, which Statistical methods can be used to predict incoming calls by a Day level at a call centre?
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1answer
22 views

Very different Neural Network test errors for same architecture

So I'm doing a time series prediction, and assessing the capability of the ANN to predict that time series. I am using Matlab's neural network toolbox functions, and the training parameters are the ...
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13 views

How forecasting is made

Can someone, please, provide some guidelines how forecasting is made about e.g. the number of TVs sold for future periods, using mobile services, etc.? What are the techniques?
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1answer
31 views

Is it reasonable to use a combination of two forecasting models for a dataset?

I used tbats to fit a model for a 3 years of historic data and the values work fine but as I did not include holidays, holiday predictions are really off. I used arima with regressor (holidays at ...
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15 views

what is the problem that auto.arima can not provide a model with seasonality for a data set which have strong seasonality?

I have 3 years of daily data which have daily and annual seasonality. I used tbats to fit a model but when I included holiday and weekend regressor, the fitted model did not change with tbats with no ...
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45 views

Obtaining the SarimaX equation from the arima coefficients

I have a SarimaX model with three regressor variables: ...
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16 views

forecasting for data excluding holiday dummies

I used tbats to fit a model to a set of 3 years of historic data for daily number of shipments moved by a trucking company. my data included double seasonality so I used tbats. However, tbats did not ...
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1answer
26 views

Is there any way to include regressors in tbats function in r? [closed]

I knew that tbtas could not consider regressor in r but I knew that Dr Hydman group were working to include this feature. I just wanted to know if it is still under work. Thanks
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1answer
34 views

How can one say if a model is poor based on RMSE value

I have a general question about the value of using RMSE to see if a forecasting model is poor. I used the forecast package in R to find forecasting models for ...
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18 views

Need to forecast a small data set. Suggest best method to go about

Hi I have sales data for previous 3 years(6 half years). I need to predict / forecast the sales for next 1-2 years. Tell me which method / model I should use. As always sales dependent on country ...
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3answers
119 views

Can predictive power be inferred from only in-sample modelling results?

I wonder if one can tell anything about predictive power of a model if model selection and estimation was done using all available data. That is, there was no data left for "out of sample" prediction ...
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23 views

prediction for data including weekly and annually seasonality and dummy variables for holidays

I have a three years of daily data for number of orders a trucking company receives everyday. Number of orders are high during weekdays and they have a huge decrease for weekend. I used msts to ...
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1answer
35 views

prediction using historic data with unusual annual trends

I have 4 years of daily data. there is a decreasing trend for the data for the first 3 years but the trend increase for the 4th year. I wanted to find a fitted model using the first 3 years and then ...
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2answers
222 views

Wrong predictions for weekend, but good predictions for weekdays

I have a set of 3 years of daily data. I saw weekly and annual seasonality in the data so I used msts time series and tbats ...
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46 views

Time series forecasting accuracy measures: MAPE and MASE

We come to this toy example showing MAPE and MASE are not consistent when measuring forecasting accuracy. Data consist of 100 white noise and 100 $AR(1)$ time series with length $N=500$, mean $\mu=1$ ...
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38 views

Stock Closing price forecasting using ARIMA Model in R ( Entry level R programmer and Statistics learner)

I am an entry level R programmer and trying to learn statistics. i have downloaded the daily stock Adjusted Close price of one stock from sep 2011 to till date. As per my study plan, i have plotted ...
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14 views

TBATS missing value error

I used tbats to find the best fit model to a 3 years of daily data. It couldnt find a model and showed the following error: " Missing values encountered. Using longest contiguous portion of time ...
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1answer
29 views

How to compute RMSE for TBATS

Some forecasting models in R give error terms as their output. But for TBATS, I couldnt find out that how I can see what the RMSE for my data set is. Is there any specific command that I have to use ...
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1answer
25 views

Data with weekly and annually seasonality but the first day in time series is not the begining of a week

I know it might look naive but I have a very basic question. I have a three years of historic data which has weekly and annual seasonality. January first as my first data is on Wednesday so my time ...
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19 views

Testing the accuracy of transformed data

I have run my data through a model in r, i ran ARIMA to forecast. The model forces a log transformation to be applied to the data. To test the accuracy of the fitted model formed by ARIMA would i need ...
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1answer
45 views

Difference between the forecast and simulate functions in the {forecast} package in R

I have been using the forecast package in R to make forecasts based on an ARIMA model and have noticed a difference in the output of the forecast and simulate functions when calculating confidence ...
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74 views

How to best make millions of forecasts using time series data?

I need to make roughly 50 million forecasts every night. The data is daily, hierarchical (~50 million base series), intermittent/sparse (for many of the time series, lots of days have 0's), and not ...
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1answer
39 views

No fitted ARIMA model

I wanted to fit an ARIMA model to a daily database for three years but auto.arima couldn't find a model and showed the following error: ...
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1answer
80 views

Forecasting a seasonal time series in R

Forecasting airline passengers seasonal time series using auto arima Hi, I am trying to model some airline data in an attempt to provide an accurate monthly forecast for June-December this year using ...
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13 views

what is the best prediction interval for a forecasting model with daily and annually seasonalitis?

If we have a data set which has daily and annually seasonality, is it reasonable to use the forecasting model for one year ahead? I mean, I want to have a 48 hours forecast for a logistic provider ...
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28 views

Creating auto arima for two following time series with two different non linear slopes

I'm trying to model (and predict) the following time series, which consist of two periods (enrollment period and non enrollment) as the following: I believe that this model should consist of two ...
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21 views

What does a fitted value mean in dshw forecasting package?

I have a double seasonal data. I wrote the following code to find the best fit model and find fitted values: orders <- read.csv("DataForR.csv", header = TRUE), NumOrders <- orders$Orders, ...
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1answer
41 views

Transforming a time series with a negative number

I have been given data to forecast however it has a negative figure within the data which then, when doing a log transformation to make the series stationary, the ARIMA script i have written won't ...
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30 views

ARIMAX model or ARDL?

I would like to study the impact the advertising of a product on its sales (weekly data for 5 years). As the final aim is to forecast what would be the impact on sales of a change in the advertising ...
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14 views

Wrong prediction for data with weekly and annually cycles

I have one year daily data which has weekly and annually seasonality. There is a problem with seasonality definition. If my weekly seasonality has 7 cycles (one for each day) and annual seasonality ...
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18 views

Different fitting models using auto arima and tbats

I have one year of daily data for forecasting. while using auto.arima to find the best fit model, it gives me ARIMA(3,1,3). However, when I used tbats to find the best fit model, it gave me the ...
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14 views

How often to update a forecasting model

If I have a data set with daily, weekly and annually seasonality, how often should I update my forecasting model? As I have heard, forecasting models out there can have a good prediction for up to a ...
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1answer
20 views

Statistical softwares providing multiple seasonality forecasting

Does anybody know which software provide forecasting with more than two seasonalities? I know R includes tools for double seasonal holt winter forecasting but I am looking for a software which can ...
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10 views

Question of Holt-Winters, parameter chosen

I am using Holt-Winters to do a time-series forecasting. The package chose gamma equal to 1 for me. I am wondering what that means. The prediction works pretty well overall. When will you use this ...
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16 views

Double Seasonal Holt winter method using dshw

I have a two weeks data set which have intraday and intraweek cycles so I decided to use dshw in r. Although it gave me a pretty good MAE and RMSE, when I wanted to see SSE, it showed me a null value. ...
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23 views

Panel data forecasting from Arellano-Bond GMM estimation

I want to come up with predictions of final energy demand per capita (fe) for a panel of countries. Explanatory variables are GDP per capita (gdp) and population density (pop) -- all variables are ...
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38 views

How to compare forecasting methods?

I have several intermittent data. Based on those data, I would like to compare several forecasting methods (Exponential Smoothing, Moving Average, Croston, and Syntetos-Boylan), and decide whether ...
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32 views

prediction of polls

Just as an example Scotland has poll to decide whether they need to be independent from UK or not. Here is BBC's summary of different polls: ...
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4answers
200 views

Forecast accuracy calculation

We are using STL (R implementation) for forecasting time series data. Every day we run daily forecasts. We would like to compare forecast values with real values and identify average deviation. For ...
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1answer
42 views

standard errors of the fitted values of a time series regression

I really want to understand how the math is working here. I am trying to get the standard error of the fitted values for a time series regression model.In the non-time series regression,I know I can ...
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1answer
55 views

Forecasting at individual versus grouped level

I have monthly usage data (spanning 3 years) for a customer base of around 200K, and I need to generate 1-month ahead forecasts for each of them. There are a couple of exogenous variables that would ...
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24 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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1answer
65 views

Under-forecasting in Regression

I have to do forecasting of sales that is how much sales of a product is going to happen in a particular store. I have time series data for last two years and doing forecasting for 2014. The variables ...
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16 views

Determining whether a dataset can be forecasted

Given a dataset $D$ representing past history of a certain variable, is there a metric $\alpha(D)$ which determines whether the dataset can be forecasted or not, i.e. $\alpha(D)$ tells us whether $D$ ...
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3answers
86 views

How to Use Neural Networks to Forecast Time Series Data with Predictor Variables?

I have browsed a lot of topics here, but the ones I see were all about forecasting a single variable, depending on its historical values. Whereas I want to predict a variable, by estimating a ...
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Transforming time series to compensate for change in variance

I have a time series (shown below) that comes from a sensor whose calibration was changed in the middle of last year. As part of this change, the sensor's reading of the variance (or volatility) of ...