Questions tagged [forecast-combination]

The process of combining different forecasts to get a better resulting forecast than any of the constituents. Simple forecast averages are often found to outperform individual forecasts in practice.

36 questions
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Combining regression models from separate data sets

What is the best way to combine regression betas from separate data sets? For example, a data set is split in two based on some fundamental characteristic, and the same two factor regression is run ...
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Forecasting with annual variable transformed into monthly

I am forecasting a series Y of monthly frequency and there is a variable X of annual frequency that would help a lot in the forecast if it had the same frequency. I decided to apply the method ...
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Weighting of multiple linear regressions in an ensemble

If I have a continuous dependent variable and N continuous predictors, and I fit all possible regressions with zero up to N variables, how should I weight those regressions for prediction? One ...
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Combining probability of default of two variable

Lets just say I have probability of defaults (PD) from two different Macroeconomic variable (MEV) with 3 different scenarios like in the picture below. What I am trying to determine is the combined ...
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Analysis for multiple products with some having 0 values for the entire dataset

My question is pertaining to automatic forecast of multiple products. I am using a combination of 2 models to forecast my timeseries data for 190 products. The values are arranged in column format. ...
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Combine mutliple predictions

This question had been asked several times in here, but I think I have something new to add. I'm interested in predicting if some specific event will happen (binary classification). I have two ...
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Evidence fusion-Dempster Shafer

I have developed four models that estimate the same state-traffic volume in 100 streets during a specific time period. I have actual volume for 25 streets to estimate compute the reliability of each ...
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Combining forecasts or distributions to form a more accurate one

Suppose you are interested in getting as good an estimate as possible for a random variable $X$, this could be for example a stock price in the future. You go to see $N$ experts, each gives you a ...
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Help in structuring problem to forecast end of testing

I need assistance, please, in structuring the following problem. (I can use the World-Wide Help Manual to do the math and the calculations, I need help in setting up the structure of the analysis). ...
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Combination of hierarchial time series forecasts with different methods - setting weights

I am trying to forecast the the number of orders for different products of a product group. I have the time series for each product. One of the problems is that some/most time series are intermittent ...
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What are the algorithms for fusing time series together

Assume I have multiple time series with the same length and the same range. What are the different algorithm used to fuse the time series together? what techniques would the best to combine them to ...
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time series forecasting in R for a period less than 2 years(18 months) which is totally random

I'm working on a project of forecasting. I have the count of the purchase order for an 18 months period of time. I'm attempting to create a forecast from time series data that has observations only on ...
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A Function to select a forecast method

I often have more than one time series to fit a model. Thanks to forecast and forecastHybrid packages they make easy to fit a ...
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How to weight several noisy estimates of the same value

If you have a variety of noisy estimates/measurements of a single value, what is the best way to combine them in order to estimate the underlying value? I have looked at "Unknown Constant in Additive ...
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Using information about covariance between ARIMA models in forecasting

I'm interested in how to incorporate information about the covariances of related timeseries from multiple univariate forecasts into each forecast. The ultimate goal of this is to implement ...
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Price change in forecast

I recently joined a online retail company and the way they have been doing forecasting and inventory management is not good at all and I'm working on improving the forecasting of the products. While ...
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Simulation based on BSTS model

currently I'm fitting different time series models and produce combined n-step-ahead forecasts. As finding prediction intervals (analytically) for combined forecasts is quite a hassle, I decided to ...
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Combine and reconcile forecasts

I am struggling conceptually with how I can best model my panel dataset. I have a set of individual data and I need to: 1) estimate the median value of the dependent variable over time in the entire ...
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Finding relevant combinations of predictors

I am currently working on a data set consisting of 300 predictors and a dependent variable. The predictors are categorical variables (taking values 0,1) and for every observation only a subset of them ...
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Optimization of Mean Absolute Error with regularization

i have two different weather forecasting systems. Each system returns values between 0 and 30 degrees. In addition i have a grounded truth set containing the real temperature values. Now i want to ...
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Approaches to average forecast in machine learning?

I have researched some approaches so far. My situation is: I have 9 different models, all targeting on the same time-series variable. Now I want to combine these 9 forecasts to estimate a better, ...
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Arguments against model or forecast combination?

Do you know any references providing arguments against model or forecast (models output) combination? Could not find anything
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Do model averaging and model combination mean the same?

I am not sure, but I guess model averaging and model combination and even forecast averaging and forecast combination are used arbitrarily in the literature... Is this only my feeling or indeed the ...
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Model averaging approach — averaging coefficient estimates vs. model predictions?

I have a basic question regarding approaches to model averaging using IT criteria to weight models within a candidate set. Most sources that I have read on model averaging advocate averaging the ...
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Weights to combine different models

I have built different classification models (logistic regression, randomforest, and xgboost) for a dataset. I would like to combine the prediction of all the models to reduce the variance and ...
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Caret package - Is it possible to compute predictions for non-optimal models?

Not sure if this post belongs here or if stack overflow would be more appropriate. I am starting to familiarize with the caret package in R which seems very powerful for the purpose of optimizing and ...
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How to implement Bayesian Model Combination?

I'm interested in formal procedure mentioned in "Turning Bayesian Model Averaging Into Bayesian Model Combination" (Kristine Monteith 2011). I have a set of $N$ "best" AIC ranked models and I want to ...
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Combining Forecasts: Best Information to Solicit from Forecasters?

Suppose Statistician $m=1$ produces a set of $h$-step-ahead point forecasts $\hat{x}_{t+h|t, 1}$ of $x_{t+h}$ where $x_{t+h} \in [0,1]$. Also, this point forecast could come with: a predictive ...
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Dangers of averaging between model approaches

I am working with some ridership data that is broken down by route, year and month. I have built and tested a whole bunch of models ranging from GLM, GEE, GENLIM, and Panel and ARIMA data models. I ...
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Assigning Weights to An Averaged Forecast

So I've been learning how to forecast over this summer and I've been using Rob Hyndman's book Forecasting: principles and practice. I've been using R, but my questions aren't about code. For the ...
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How does Weka combine the decision trees in a random forest?

When building the random forest, I am wondering if Weka combine the decision trees by averaging their probabilistic prediction or if Weka let each decision tree vote for a unique class?
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Combining probabilities/information from different sources

Lets say I have three independent sources and each of them make predictions for the weather tomorrow. The first one says that the probability of rain tomorrow is 0, then the second one says that the ...
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More Statistical Way to Average N Predictions

I've run a RandomForestRegressor (Scikit Ensemble) over N loops, each time changing the random seed and therefore changing the train test split. This way I've N sets of predictions (M predictions for ...
Suppose I'm trying to predict $Y$ (a real number) and I have $n$ experts with guesses $Y_1,...Y_n$. Each prediction is a reasonable guess as to the value of Y in itself (hence the name "expert"), but ...
Framework. Fix $\alpha\in ]0,1[$. Imagine you have $n$ $\alpha$-quantile forecast methodologies that give you, at time $t$ for look ahead time $t+h$, an estimation of the quantile of wind power. ...