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

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Let's talk sales forecasts - integrating a time series model with subjective “predictions/ leads” from sales team

I've learned a lot about time series forecasting this previous year, but one thing that's still a bit lacking in terms of a formal system is integrating a future sales projection into an existing time ...
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17 views

Multivariate stochastic time series forecasting in R

Hi I have a multivariate time series like this ...
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17 views

best way of univariate prediction for sparse data

I have a client who has sparse hourly data (by sparse I mean there are too many hours with 0 calls). I used TBATS in R to forecast hourly data for them. Regardless of the point forecast, the actual ...
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21 views

Arima Models Diagnostics

I'm doing a forecasting using seasonal ARIMA method. I'm using astsa package in r and I'm testing two models that I can't decide which one is better to use than the other The ACf and PACF for the ...
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30 views

AIC versus cross validation in time series

I am interested in model selection in a time series setting. For concreteness, suppose I want to select an ARMA model from a pool of ARMA models with different lag orders. The ultimate intent is ...
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13 views

Prediction intervals for mixture models for time series forecasting - is it really an average of the prediction intervals of the averaged models?

I'm trying to find out how to do forecasting with a mixture model (averaging the forecasts of an ets, an arima and an ...
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27 views

Diebold Mariano test for multiple forecasts in R

I am trying to do Diebold Mariano test for multiple forecasts. How do you implement this in R? Thanks a lot.
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7 views

Multi-step ahead forecasting with generalized additive models

I would like to build forecast models using generalized additive models (GAM) with AR(p) correlation specification and explanatory covariates, using similar methods to those described in this blog ...
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0answers
10 views

Forecasting hierarchical time series with different model for each bottom time series?

I have univariate time series data for each country of the world. I am interested in forecasting at both the global and individual-country levels. Although the value being measured is the same, the ...
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1answer
28 views

Where do you find info about which predictive distribution an algorithm uses for forecasting?

I am trying to fit a mixture model to a time series in order to make forecasts. I'm told that this is quite straightforward as long as the predictive distributions used by the component algorithms ...
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18 views

Passing different forecasting method to hierarchical time series forecast in R? [migrated]

I have a hierarchical time series, the bottom level series of which all exhibit intermittent demand. It seems advantageous to use Hyndman's HTS package for optimal combination within the hierarchy. It ...
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0answers
7 views

How to add NA's to the data not available for some dates? [migrated]

I have a data for short term electricity load forecasting. I have to clean the data, adding NA's in the data for dates( and blocks) with no data. For example: 1st case: with some dates missing: ...
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1answer
18 views

One-Step ahead predictive likelihood for time series forecasting

I am still new to Bayesian forecasting, so I am hoping to get some clarification on a simple concept (by the sounds of it). Suppose that we are interested in forecasting some time series one-step ...
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1answer
40 views

Issues in auto.arima algorithm when using external regressors and outlier correction

auto.arima is an automatic arima modeling function in forecast package in R that uses information criterion(example: AIC/BIC) to ...
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0answers
8 views

tbats{forecast} in R gives strange predictions for some folds in cross validation

My daily data shows weekly and yearly seasonality, so I decide to try the tbats function. When I first fit the model with all the data, it worked fine. However ...
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0answers
23 views

Difference in forecast accuracy between numeric vector and time series [closed]

I'm trying to compute the accuracy for my forecasting but I found that the accuracy changes when I convert my test data from time-series to numerical vector, especially as measured by MASE and Theil's ...
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1answer
36 views

Forecasting daily demand for next year

I have two years daily demand data, corresponding to which I have to forecast the daily demand for next year. I am new to time series, and used Arima model for this purpose. But it predicts only about ...
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0answers
13 views

A fast convergence method for inverse problem

I have an inverse problem that is very CPU demanding. In this problem I have two types of data: 1-static, 2-Dynamic. First I use a method and create some models based on the static data. Clearly, ...
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0answers
9 views

Triple exponential smoothing handling 0 as input

I am using triple exponential smoothing multiplicative method for forecasting of input numbers. I have past 2 years of data which has a few '0' as entries. So when I run the forecast it gives me a ...
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0answers
9 views

VAR model selection for forecasting one variable

Suppose I have a VAR model for variables $x_1$ through $x_K$. I will use the model to forecast $x_1$ a few steps ahead and will do this iteratively rather than directly. I am not interested in ...
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0answers
12 views

Better forecast on seasonal type and lessthan 1 year of data

I have a client which started on december 2014 and they are only capable of sending their sales during middle and last day of the month. I used exponential smoothing to get their forecast sales. The ...
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0answers
10 views

Why ets() function in R is not fitting a seasonal model? [migrated]

I am using ets() function in R to fit the seasonal model.I have a weekly sales data.I can see clearly in my data that it has seasonal patterns along with trend. ...
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0answers
21 views

Robust Measures for Forecast Accuracy

I am doing a forecast using robust exponential smoothing methods and to determine / measure the forecast accuracy I want to use robust measurements as well. As I am not really familiar with robust ...
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0answers
11 views

How to forecat a ARMAX model with 1 step ahead forecast in R?

I have divided my time series to 2 parts and I have used first part Y1TS[1:n2] for model fitting and Y1TS[n2:n1] for forecasting ...
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22 views

Forecasting Sales with Multiple Regression

I want to forecasting week sales by using Multiple Regression. Since I have factors that influences weekly sales. I know when we use commercials, reduce the price, which placements in the stores, ...
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33 views

Understanding forecast horizon for Diebold-Mariano tests

I have a problem understanding the parameter horizon of the function dm.test {forecast} in my particular setting. Background: My goal is to forecast energy consumption for individual households. The ...
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6 views

Using nonstationary independent variables in a panel survival model

I am debating with someone over the appropriate use of time series variables in a survival model. We have an unbalanced panel with a survival outcome (0,1), time-invariant features of the panel units, ...
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1answer
30 views

Which one to compromise between MAPE and Adj R square in multiple regression

I'm trying to forecast sales of a product based on the other variables like Competitor sales, Fuel Price and CPI (Consumer Price Index). The below given output (based on 1 to 44 months) gives me the ...
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14 views

Forecasting with a VAR estimated by GLS versus OLS

Suppose I have a VAR model with different regressors in different equations (this could be due to restricting some coefficients of a full VAR($p$) model to zero or having some different exogenous ...
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23 views

How to forecast a 95% prediction interval for a variable?

I have a data set containing the height of 1000 students for 4 years (one measurement for each student for each year), from 2011 to 2014. I want to forecast the mean height for these students for the ...
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32 views

Best way to forecast hourly data

I have a time series of hourly data for 3 years. I want to find hourly forecasts using this set of historic data. My data has hourly, daily and annual seasonality. I first read my data into a ...
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0answers
44 views

Accuracy function in R [migrated]

I Want to compute the accuracy of a numerical vector that contains 12 forecasts but I get this result with a warning. ...
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0answers
16 views

How to predict values? [duplicate]

I have a simple time series with at least a measurement a day. I would like to know if there are algorithms that can deal with missing values and measurements that are not taken always at the same ...
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0answers
8 views

Store outputs of forecast [migrated]

I'm using a forecast() function in R many times with loop (12 months) for but I want to use accuracy to compare forecast for horizon time =12 and one-step ahead. My problem is how to store the results ...
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0answers
17 views

Probabilistic forcasting

My question relates to probabilistic forecasting. How does one actually go about computing a forecast? Lets say I have some data that can be modelled by a specific distribution, and the values of the ...
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1answer
45 views

Forecasting in Stata

I am working with time series data and fitting an autoregressive model using OLS. For reference, here is my price data for the commodity (I am not sure how to better format data for this site): ...
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1answer
95 views

Daily Ticket Sales

I looked around to see if there was a similar question, but couldn´t find one. I apologize if there is one and I missed it. I have the amount of ticket sales per day for 10 different events. The ...
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5answers
527 views

Best method for short time-series

I have a question related to modeling short time-series. It is not a question if to model them, but how. What method would you recommend for modeling (very) short time-series (say of length $T \leq ...
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1answer
42 views

Time series with multiple subjects and multiple variables in R

I'm having trouble finding a time series technique to deal with a data set I am working on. It contains multiple subjects and multiple variables, not all of which will likely be part of the time ...
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2answers
84 views

What criteria tell us that the prediction of a model is reliable

What criteria can be used to tell whether the prediction of a model will be more reliable than other specifications. Background: We have data with $N$ computers. However, prices available only ...
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1answer
69 views

What is a good model for revenue managment / price optimization problem

I am trying to create a dynamic pricing model to optimize revenue for a hypothetical business. Lets say I have an application that connects dog walkers to people who want to pay for their dog to get ...
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24 views

Forecasting method for retail [closed]

What are forecasting methods that will fit a retail industry? particularly in school supply type. I'm thinking of time series since it has a seasonal demand, the prediction is more accurate. Are there ...
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0answers
27 views

Vector autoregression (VAR)

In a VAR I use two price-variables which are co- integrated. Is that a problem, the literature is somewhat mixed? With three lags there are no problems with serial correlation between them ...
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0answers
20 views

How to evaluate a Bayesian forecast?

Suppose that I have a predictive posterior, which is an attempt to predict some one-step ahead forecasted value $\hat{y}_{T+1}$. How do I assess if my posterior has done a good job or not? If we had ...
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1answer
26 views

Prediction in VAR models

I am currently developing a Vector Autoregressive Model, and I have the model fully specified as follows: $$X_t=AX_{t-1} +Z_t$$ where $X$ and $Z$ are $n \times 1$ column vectors, and $A$ is an ...
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0answers
41 views

Forecasting in r using ets() of forecast package..seasonality and trend not detected

I have tried forecasting in R using ets(). I let ets choose the best model for my data. The problem is i observed that eventhough the data shows an increasing trend and exhibits seasonality, ets is ...
3
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2answers
96 views

Kernel density estimation vs. machine learning for forecasting in large samples

This is a hypothetical and pretty general question. Apologies if it is too vague. Suggestions on how to better focus it are welcome. Suppose you are interested in the relationship between one ...
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3answers
66 views

How to take advantage of multiples series with the same behaviour for forecasting?

I'm quite new to statistics and forecasting, and I have to build a model to forecast monthly sales of different related products in a bunch of cities. Seasonal ARIMA seams to be a good model for ...
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1answer
54 views

Comparing Time Series Forecast Models

I'm to write a short report on Time Series forecast comparison. I'm a beginner in the field. I want to investigate how one chooses which model is better than the other based on the forecast results. ...