Tagged Questions

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

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0
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1answer
19 views

Optimization failure in HoltWinters [on hold]

I am using HoltWintersto fit the exponential model on the data. The data shows trend as well as seasonal pattern.Getting the following error message: ...
2
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0answers
19 views

Forecastability and Coefficient of Variation

I'm trying to get a sense check here. When determining "forecastability" for sales data, I tend to use the CV. However, this is highly susceptible to seasonality and outliers. As such, I was ...
0
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0answers
24 views

Forecasting a solar data using arima in R [on hold]

I have a solar data collected from a PV plant for the period 2009.the method for forecasting as suggested for me is to use a training set for instance from 01/01/2009 to 30/04/2009 and a test period ...
7
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2answers
365 views

Is it unusual for MEAN to outperform ARIMA?

I'm relatively new to forecasting so I hope this isn't a ridiculous question. I recently applied a range of forecasting methods (MEAN, RWF, ETS, ARIMA and MLPs) and found that MEAN did surprisingly ...
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0answers
23 views

Making a neural network model more sensitive to one of its several inputs

I am currently using neural network methods in R to model energy consumption (response) based on temperatures, previous consumption values and weekend dummy variables (inputs). Unfortunately, the ...
0
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0answers
20 views

Techniques for comparing two windows of data in a time series

I'm working on a small independent project in R, trying to make my own (very crude) forecasting method. The general idea of the component that is giving me trouble is trying to compare two windows of ...
1
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0answers
10 views

Training/ Test Data with Time Series Model — Forecast with Training Model, or with Model based on Full Data?

Okay, I have a couple books on time series forecasting, but perhaps I need to read a couple more. Here's my question. You want to be able to validate a forecasting model. So you split the data into ...
0
votes
1answer
24 views

R times series — correct use of forecast() and accuracy() in forecast package

Cross-posting this from Stack Overflow, because it's a bit of a stats/ technology cross-over. I'm relatively new to R and the forecast package I believe authored by Rob Hyndman. I'm having trouble ...
2
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2answers
112 views

What is the distinction between short term and long term forecasting?

I often see forecasting methods described as long term or short term methods. I assume the difference between short term and long term forecasting cannot just be the amount of time. I assume this ...
1
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0answers
22 views

Hold out sample vs. cross validation for time series, and how to perform in R

I think out-of-sample validation testing for accuracy is essential in initially judging what time-series forecasts to use. In any case, I've been doing some reading on the two most common methods, ...
0
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0answers
23 views

autocorrelation in evaluating time series forecasts

I'm having some trouble wrapping my head around whether using Holt-Winters ETS or an ARIMA model for forecasting sales figures (which are highly seasonal). I'm been using R and the Forecast package ...
0
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0answers
13 views

VAR model for price forecasting in multiple time-series context. How to get “real figures” as forecasts?

Sorry for the rather long introduction, but since I was (legitimately) critizised for not explaining my cause and questions enough, I will do so now. I would like to conduct a (price)-forecast based ...
0
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1answer
46 views

Transfer function in forecasting models - interpretation

I am occupied with ARIMA modelling augmented with exogenous variables for promotional modelling purposes and i have hard time explaining it to business users. In some cases software packages end up ...
1
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1answer
33 views

Time series modelling

Here is my problem: I basically have 20 or so variables (I have 1000 of these values over an increasing time axis). I want to calculate the weights of these input variables. I am going to try Linear ...
0
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0answers
20 views

time series definition for time between failure

I recently started on forecasting time-between-failure for failure of different components in a truck. I saw a few papers which used ARIMA to do the forecasting for number of failures at specific time ...
1
vote
1answer
57 views

Interpretation of mean absolute scaled error (MASE)

Mean absolute scaled error (MASE) is a measure of forecast accuracy proposed by Koehler & Hyndman (2006). $$MASE=\frac{MAE}{MAE_{in-sample, \, naive}}$$ where $MAE$ is the mean absolute error ...
0
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0answers
19 views

Generalized likelihood ratio test

Does anyone use the generalized likelihood ratio test for detecting a sudden change in time series forecasting (ARIMA Model)? A paper by Bonne Zhu uses this technique for anomaly detection, but I ...
0
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0answers
22 views

Beta Binomial Distribution with a priori $\alpha$ and $\beta$ to Account for Probability Forecasts

I am trying to use a beta binomial distribution to calculate how much a single vote would count in a 2-choice election, given $n$ voters and a $p$ forecast: $ f(\lceil\frac{n}{2}\rceil;n,p) $ where $ ...
1
vote
1answer
51 views

How do I forecast using exponential smoothing past one data point?

ALL of the examples go through a lot of explanation then only forecast one data point. I need to forecast more than on data point, but I can't find an example anywhere to do that. If you use the ...
0
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0answers
10 views

1-period rolling out of sample forecast for dynlm model

I have six monthly time series that span from January 2005 until June 2014. I'm trying to test two different dynamic linear models and compare how they perform in one period ahead forecasting. I have ...
1
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0answers
27 views

Forecast of spot electricity prices

I recently started a job in power trading. But due to a sudden change in employment I am required to work on econometric models to gauge the supply and demand side of national power markets. So ...
1
vote
1answer
24 views

comparison of forecasting models for daily data (frequecy=365)

I have 852 days of daily attendance data and need to use the first 800 days data to predict the next 52 days and match it with my actual values. How do i decide which is the best model to use for ...
0
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1answer
25 views

combining subjective probability estimates and statistical estimates for forecasting

At the end of the year forecasters usually struggle year to predict landing estimate for the financial year due to variety of reasons including volatility, unreliable demand projections, inventory ...
0
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1answer
23 views

Average time series data (summarize) increasing slope of line

We are working on time series data forecasting. Our input data set is large, so thought to average two consecutive data points and reduce it to half the size. But we have observed that average values ...
0
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0answers
33 views

Formula behind forecast in R

Can anyone tell me the formula behind the forecast function in R? Preferably in the form easily understood by mathematicians (e.g x_t, θ etc) Here is my code in ...
0
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0answers
24 views

simple exponential smoothing with drift

I have researched all over the text books and software (R/SAS/SPSS), but I have not encountered Simple Exponential Smoothing (SES) with a drift ? Is it possible to add a drift term to Simple ...
0
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0answers
21 views

Forecast accuracy using MASE

In the forecast library in R, when I try to find the accuracy of my fit ("fc" in example below), I get a MASE value of 0.567584 for Training set and 0.633166 for Test set ("test" in example below). ...
0
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0answers
21 views

Understanding / Interpreting VARselect function in R

Atm I am playing around with VAR-Models and I was asking myself how to properly use the VARselect function. My question is the following: What should I give R as y? In the Help it just states "Data ...
2
votes
1answer
52 views

How does a moving average model for forecast work?

Excuse me for the question, I'm reading "Forecasting: principles and practice" by Rob J Hyndman. I'm stuck on this chapter: https://www.otexts.org/fpp/8/4 which briefly explains how a moving average ...
0
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0answers
17 views

Creation of Demand Forecasting Hierarchy

I have a question concerning the creation of hierarchies for demand forecasting purposes. As i have read one approach is to create one "super" hierarchy for the whole business e.g. Total Demand --> ...
1
vote
1answer
28 views

Interpretation of Demand Forecasting Hierarchy

I am occupied with hierarchical demand forecasting (mainly about consumer packaged goods) and i have a question about the interpretation of its structure. Let us assume that the hierarchy is as ...
0
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0answers
47 views

3 month forecast for commodity prices in R - general help for approach

In the following I'll describe my undertaking as detailed as possible in order to provide you enough information. Please keep in mind (when answering) that neither I'm a matematician nor a ...
0
votes
1answer
29 views

Can I use this equation for prediction?

I've got a question. Below you see a graph which shows the regression equation between construction activities in the private sector (X axis) in £bn and the total amount of all construction activities ...
0
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0answers
8 views

What information should be in a paper on the analysis of maintenance of fleet system

I need to write a conference paper on recent analysis of two data sets. One data set contains measurements of vehicle operating characteristics for a fleet of vehicles. The 2nd data set contains the ...
1
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1answer
64 views

Weekly seasonality model by ARIMA+Fourier terms+dummies

This is a long post but it is not conceptually difficult. Please bear with me. I am trying to model the seasonality of production volume of an agricultural commodity. I do not care about the ...
0
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0answers
10 views

Event level driven response modeling

I am investigating operational and maintenance data for a fielded system. There is a year worth of data. The operational data has been reduced to fault indications, which are triggered when ...
1
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0answers
38 views

auto.arima and Arima (forecast package)

I am facing a strange issue with auto.arima. On a dataset named data, I run the following code ...
0
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0answers
24 views

Time series forecasting with multiple series with constraints

Hello and thanks in advance. I am using ARIMA or VAR models to forecast sales revenue. Suppose I have three different time series in each of three categories (making 9 series in total). The first ...
-2
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0answers
17 views

Forecasting in R X Axis [migrated]

Good day How do I change the x axis so that it shows the year and month? At the moment the x axis doesn't look right and comes up with 2014.0, 2014.5 and 2015.0. I want to use the forecast package ...
3
votes
3answers
179 views

How do I handle nonexistent or missing data?

I tried a forecasting method and want to check if my method is correct or not. My study is comparing different kinds of mutual funds. I want to use the GCC index as a benchmark for one of them but ...
0
votes
0answers
18 views

how could i handle with missing data or non existent data? [duplicate]

i tried a forecasting method and i want to check if it is correct or not and why? my study is about evaluating mutual funds for two kind of them it is a comparative study and i wan to use gcc index ...
1
vote
0answers
34 views

Regression model for predicting life expectancy

I have average life expectancy at birth data for an 8 year period and I would like to use that 8 year period to predict the trend for average life expectancy for the next 5 years. I would then like to ...
0
votes
0answers
14 views

error for xreg and newxreg matrix size in an arima model

I am using auto.arima to forecast a daily data and used holiday and weekday dummies as regressors. I am getting an error which does not make sense. When I want to predict a 7 step ahead forecast, it ...
1
vote
0answers
31 views

Why only full ARIMA models in auto.arima?

It seems that the auto.arima() function in the forecast package in R only considers full ...
0
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0answers
23 views

Adding predictor variables and/ or systematic judgement to time series forecasts

I have a ways to go with my forecasting general education --- but I'm doing a seasonal time-series forecast for predicting sales order volumes. It's mostly software sales, which does have a ...
1
vote
0answers
26 views

Does the density of daily data impact forecast accuracy?

I know it might be trivial but does the density of daily values impact the forecast accuracy? For example, if a call center receives less than 50 calls for weekdays and less than 10 calls for weekend, ...
0
votes
1answer
88 views

Theories how they arrived at this Ebola growth forecast? Not regression

The 21,000 estimate for Oct. was certainly not via quad or power regression. I wonder how they got that number? ...
0
votes
0answers
18 views

time-series forecasting - predicting av. error intervals

I should start with the disclaimer I'm not proficient with R or heavier statistical terminology, sadly! Nevertheless I create sales forecasts (using different methods such as holt-winters), and I'm ...
1
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0answers
90 views

In-Sample vs. Out-of-Sample One-Step Ahead Forecasts

I'm fairly new to forecasting but I find all of this quote fascinating and hope to learn something from all of you. I have 500 observations and I'm tasked with the following: "compute recursive ...
0
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0answers
60 views

How to implement a simple Bayesian Network for Time Series Data?

I'm a computer science grad student, with not much knowledge in Bayesian statistics, so I'm seeking for guidance for the simplest start. I have 10 variables, like demand, price etc. and I want to ...