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.

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15 views

Time Series Forecast for a time series getting updated

I am working on a forecasting problem, where i am planning to forecast the value for the current time step (real value 43 in data below in a[4] column). The data is in the form of values at each ...
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How can I calculate Conditional expectation using copula

Let X, Y two time series and $F_{i, \beta_i}$ the marginal distribution of residual of each time series and beta is vector of their parameter. I studied the dependence between this two series using ...
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Part Univariate and part Multivariate Timeseries forecasting problem

I have a forecasting problem: Data from 1-1-2015 to 8-31-2019 is Univariate (Weekly) Data from 1-1-2017 to 8-31-2019 is Multivariate (Weekly) Final predictions need to be made from 9-1-2019 to 12-...
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Is Bregman Divergence useful in applications for combining (marginalized) probability densities of transformed variables?

I see a lot of theoretical results about the right way to think about solving for $P(y_0, y_1, ...)$ given information about "marginals" (i.e. transformed views of the underlying $y$) $P(f_i(y)), i=1,\...
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99 views

Forecast combination using optimal weights

I am struggling with a case where I am supposed to calculate optimal forecast weights of two forecasts. We have fitted the models on a training set (time series) and want to calculate optimal weights ...
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21 views

Forecast package in R

I have one question which is maybe very simple. So my question is does models from forecast package in R (e.g auto.arima,ets,tbats,nnetar etc) are machine learning models or not?
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Forcasting with only total sale of product?

is it possible to make a forecast when you only have the total sale (of last year) per product variant? I would like to make a forecast for the next year 2021. So for example, if last year's sale per ...
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106 views

Combination of correlations: How to correlate compositions?

How to correlate a set of compositions to a same-sized set of estimates of these compositions? -> composition(estimated) vs composition(real) Imagine you have a mixture of 5 liquids A+B+C+D+E, ...
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Combining different type of predictor

At my framework, I have three different types of the predictor. 1) beta function, Artifical neural network, and an exponential function. Each of these model estimate different value. For example, beta ...
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49 views

How do I weight multiple forecasts based on Mean Absolute Percentage Error (MAPE)?

I have 3 forecasts that have different Mean Absolute Percentage Error values that were averaged for each forecast over a 6 month period at a monthly cadence against end of month actuals. How would I ...
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1answer
46 views

Averaging individual predictions in a group

I created linear model to give prediction for a team member (individual). Can I use this model to give average (individual) prediction in a team by providing average values of features among team ...
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Forecasting time point not value

I have a simple question. when we want to forecast a time series, we always focus on the value of series in future. But could we forecast time point of spesific value? For example I would like to ...
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54 views

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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249 views

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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1answer
64 views

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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1answer
25 views

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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121 views

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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1k views

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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830 views

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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1answer
91 views

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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566 views

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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2answers
86 views

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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299 views

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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51 views

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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149 views

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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568 views

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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1answer
125 views

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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3answers
104 views

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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463 views

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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2answers
466 views

Time series forecasting with a combination of methods

So, i read this article: https://www.r-bloggers.com/timeseries-forecasting-using-extreme-gradient-boosting/?utm_source=feedburner&utm_medium=email&utm_campaign=Feed%3A+RBloggers+%28R+bloggers%...
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1k views

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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650 views

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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1answer
820 views

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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976 views

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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63 views

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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35 views

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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3k views

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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1k views

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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13k views

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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2answers
1k views

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 ...
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680 views

Model averaging in prediction — “Wisdom of the Crowd”

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 ...
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901 views

How to make a combination (aggregation) of quantile forecast?

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. ...