New Methods of Quality Control

Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors

Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999) · Statistical Science · doi:10.1214/ss/1009212519 · Cited by 4,118 · see citing works

The Combination of Forecasts

Bates, J. M., & Granger, C. W. J. (1969) · Journal of the Operational Research Society · doi:10.1057/jors.1969.103 · Cited by 3,201 · see citing works

Handbook of Economic Forecasting

(2013) · Handbook of economic forecasting · doi:10.1016/b978-0-444-53683-9.00023-2 · Cited by 1,290 · see citing works

Invited review combining forecasts—twenty years later

Granger, C. W. J. (1989) · Journal of Forecasting · doi:10.1002/for.3980080303 · Cited by 322 · see citing works

MODEL AVERAGING IN ECONOMICS: AN OVERVIEW

Moral‐Benito, E. (2013) · Journal of Economic Surveys · doi:10.1111/joes.12044 · Cited by 249 · see citing works

Combining forecasts – forty years later

Wallis, K. F. (2010) · Applied Financial Economics · doi:10.1080/09603107.2011.523179 · Cited by 158 · see citing works

Time-varying combinations of predictive densities using nonlinear filtering

Billio, M., Casarin, R., Ravazzolo, F., & van Dijk, H. K. (2013) · Journal of Econometrics · doi:10.1016/j.jeconom.2013.04.009 · Cited by 152 · see citing works

A Bayesian approach for quantification of model uncertainty

Park, I., Amarchinta, H. K., & Grandhi, R. V. (2010) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2010.02.015 · Cited by 149 · see citing works

Chapter 1 Bayesian Forecasting

Geweke, J. F., & Whiteman, C. H. (2006) · Handbook of economic forecasting · doi:10.1016/s1574-0706(05)01001-3 · Cited by 122 · see citing works

Depression as a dynamical disease

Pézard, L., Nandrino, J., Renault, B., Massioui, F. E., Allilaire, J., Müller, J., Varela, F. J., & Martinerie, J. M. (1996) · Biological Psychiatry · doi:10.1016/0006-3223(95)00307-x · Cited by 99 · see citing works

Model Averaging in EconomicsPreprint

Moral‐Benito, E. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1926669 · Cited by 82 · see citing works

Fisher's game with the devil

Senn, S. J. (1994) · Statistics in Medicine · doi:10.1002/sim.4780130305 · Cited by 71 · see citing works

Improving time series forecasting: An approach combining bootstrap aggregation, clusters and exponential smoothing

Dantas, T. M., & Oliveira, F. L. C. (2018) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2018.05.006 · Cited by 65 · see citing works

Time-Varying Combinations of Predictive Densities Using Nonlinear FilteringPreprint

Billio, M., Casarin, R., Ravazzolo, F., & van Dijk, H. K. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.2172254 · Cited by 62 · see citing works

Refined analysis and prediction of natural gas consumption in China

Liang, T., Chai, J., Zhang, Y., & Zhang, Z. G. (2019) · Journal of Management Science and Engineering · doi:10.1016/j.jmse.2019.07.001 · Cited by 56 · see citing works

Quantification of model-form and predictive uncertainty for multi-physics simulation

Riley, M. E., & Grandhi, R. V. (2010) · Computers & Structures · doi:10.1016/j.compstruc.2010.10.004 · Cited by 52 · see citing works

Gumbel based p-value approximations for spatial scan statistics

Abrams, A. M., KLEINMAN, K. P., & Kulldorff, M. (2010) · International Journal of Health Geographics · doi:10.1186/1476-072x-9-61 · Cited by 52 · see citing works

Forecast combination in a dynamic setting

Coulson, N. E., & Robins, R. P. (1993) · Journal of Forecasting · doi:10.1002/for.3980120106 · Cited by 45 · see citing works

Nonlinear EEG Changes Associated with Clinical Improvement in Depressed Patients

Thomasson, N., Pézard, L., Allilaire, J., Renault, B., & Martinerie, J. M. (2000) · Nonlinear Dynamics Psychology and Life Sciences · doi:10.1023/a:1009580427443 · Cited by 39 · see citing works

Quantification of Modeling Uncertainty in Aeroelastic Analyses

Riley, M. E., Grandhi, R. V., & Kolonay, R. M. (2011) · Journal of Aircraft · doi:10.2514/1.c031059 · Cited by 39 · see citing works

Combining multiple algorithms in classifier ensembles using generalized mixture functions

Costa, V. S., Farias, A. D. S., Bedregal, B., Santiago, R. H. N., & Canuto, A. M. P. (2018) · Neurocomputing · doi:10.1016/j.neucom.2018.06.021 · Cited by 37 · see citing works

Bayesian Calibration of Generalized Pools of Predictive Distributions

Casarin, R., Mantoan, G., & Ravazzolo, F. (2016) · Econometrics · doi:10.3390/econometrics4010017 · Cited by 25 · see citing works

Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty

Qiu, Y., Wang, Z., Xie, T., & Zhang, X. (2021) · Journal of Empirical Finance · doi:10.1016/j.jempfin.2021.03.003 · Cited by 25 · see citing works

Invited Review: Combining Forecasts – Twenty Years Later

Granger, C. W. J. (2001) · Cambridge University Press eBooks · doi:10.1017/cbo9780511753961.022 · Cited by 25 · see citing works

Process identification for time series modelling in urban and regional planning

Bennett, R. J. (1974) · Regional Studies · doi:10.1080/09595237400185151 · Cited by 25 · see citing works

Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models

Papacharalampous, G., Koutsoyiannis, D., & Montanari, A. (2019) · Advances in Water Resources · doi:10.1016/j.advwatres.2019.103471 · Cited by 25 · see citing works

Modern approaches to shipborne ocean color remote sensing

Garaba, S. P., Voß, D., Wollschläger, J., & Zielinski, O. (2015) · Applied Optics · doi:10.1364/ao.54.003602 · Cited by 22 · see citing works

Forecasting Inflation with the Phillips Curve: A Dynamic Model Averaging Approach for Brazil

Ferreira, D., & Palma, A. A. (2015) · Revista Brasileira de Economia · doi:10.5935/0034-7140.20150021 · Cited by 21 · see citing works

Chapter 2 Combining Predictors & Combining Information in Modelling: Forecasting US Recession Probabilities and Output Growth

Clements, M. P., & Galvão, A. B. (2006) · Contributions to economic analysis · doi:10.1016/s0573-8555(05)76002-8 · Cited by 19 · see citing works

Combining Predictive Densities Using Bayesian Filtering with Applications to US Economics DataPreprint

Billio, M., Casarin, R., Ravazzolo, F., & van Dijk, H. K. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1735421 · Cited by 14 · see citing works

Chapter 1 Forecasting Annual UK Inflation Using an Econometric Model over 1875–1991

Hendry, D. F. (2008) · Frontiers of economics and globalisation · doi:10.1016/s1574-8715(07)00201-1 · Cited by 13 · see citing works

Hybrid model with dynamic architecture for forecasting time series

Gomes, G. S. S., Maia, A. L. S., Ludermir, T. B., de Carvalho, F. D. A. T., & Araujo, A. F. R. (2006) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2006.1716613 · Cited by 12 · see citing works

Forecast Bitcoin Volatility with Least Squares Model Averaging

Xie, T. (2019) · Econometrics · doi:10.3390/econometrics7030040 · Cited by 11 · see citing works

Density Forecasting

Bassetti, F., Casarin, R., & Ravazzolo, F. (2019) · Advanced studies in theoretical and applied econometrics · doi:10.1007/978-3-030-31150-6_15 · Cited by 10 · see citing works

PREDICCIÓN DE SERIES TEMPORALES CON REDES NEURONALES: UNA APLICACIÓN A LA INFLACIÓN COLOMBIANA

Santana, J. C. (2006) · Revista Colombiana de Estadística · Cited by 10 · see citing works

An algorithm for automatic selection and combination of forecast models

García-Aroca, C., Mayoral, M. A. M., Morales, J., & Segura, J. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121636 · Cited by 8 · see citing works

Bayesian Model Averaging

Hofmarcher, P., & Grün, B. (2019) · Advanced studies in theoretical and applied econometrics · doi:10.1007/978-3-030-31150-6_12 · Cited by 8 · see citing works

Optimal forecasting accuracy using Lp-norm combination

Giacalone, M. (2021) · METRON · doi:10.1007/s40300-021-00218-5 · Cited by 8 · see citing works

The Impact of Organizational Citizenship Behavior on Organizational Performance of Vietnamese Universities during the Covid-19 Pandemic: The Moderating Role of Transformational Leadership

(2022) · Journal of System and Management Sciences · doi:10.33168/jsms.2022.0301 · Cited by 7 · see citing works

What To Do About Atheoretic Lags

Cranmer, S., Rice, D. R., & Siverson, R. M. (2015) · Political Science Research and Methods · doi:10.1017/psrm.2015.36 · Cited by 7 · see citing works

Quantification of Modeling Uncertainty in Aeroelastic Design

Riley, M. E., & Grandhi, R. V. (2010) · AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (MAO) · doi:10.2514/6.2010-9276 · Cited by 7 · see citing works

Bayesian model averaging

Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (2010) · Statistics, a series of textbooks and monographs · doi:10.1201/ebk1439836149-c9 · Cited by 8 · see citing works

Improved Methods for Combining Point Forecasts for An Asymmetrically Distributed VariablePreprint

Karagedikli, Ö., Vahey, S. P., & Wakerly, E. C. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3332882 · Cited by 7 · see citing works

Applying Uncertainty Quantification to Structural Systems: Parameter Reduction for Evaluating Model Complexity

Locke, R., Kupis, S., Gehb, C. M., Platz, R., & Atamturktur, S. (2019) · Conference proceedings of the Society for Experimental Mechanics · doi:10.1007/978-3-030-12075-7_28 · Cited by 6 · see citing works

Are Forecast Combinations Efficient?Preprint

Pincheira, P. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.2039670 · Cited by 5 · see citing works

A New Algorithm in Bayesian Model Averaging in Regression Models

Fan, T., Wang, G.-T., & Yu, J.-H. (2013) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2012.700750 · Cited by 4 · see citing works

A spatial model averaging approach to measuring house prices

Greenaway‐McGrevy, R., & Sorensen, K. (2021) · Journal of Spatial Econometrics · doi:10.1007/s43071-021-00013-4 · Cited by 4 · see citing works

Theory and applications of competitive prediction

Zhdanov, F. (2011) · Royal Holloway Digital Repository (Royal Holloway University of London) · Cited by 4 · see citing works

Combining Predictive Densities Using Nonlinear Filtering with Applications to US Economics DataPreprint

Billio, M., Casarin, R., Ravazzolo, F., & van Dijk, H. K. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1967435 · Cited by 4 · see citing works

Quantification of Multiple Types of Uncertainty in Physics-Based Simulation

Park, I. (2012) · CORE Scholar (Wright State University) · Cited by 3 · see citing works

Bayesian model averaging in longitudinal regression models with AR(1) errors with application to a myopia data set

Fan, T., & Wang, G.-T. (2014) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2014.891205 · Cited by 3 · see citing works

RELIABILITY TEST PLANS IN THE CASE OF DEPENDENT OBSERVATION BASED ON EXPONENTIAL FAILURE MODEL

(2015) · Journal of Statistics Advances in Theory and Applications · doi:10.18642/jsata_7100121497 · Cited by 3 · see citing works

Quantification of Multiple Types of Uncertainty in Computer Simulation Using Bayesian Model Averaging

Park, I., & Grandhi, R. V. (2010) · AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (SDM) · doi:10.2514/6.2010-2512 · Cited by 3 · see citing works

Bayes Factors and the Observational Method

Baecher, G. B., & Christian, J. T. (2015) · IOS Press eBooks · doi:10.3233/978-1-61499-580-7-939 · Cited by 3 · see citing works

Forecasting volatility: double averaging and weighted medians

Reschenhofer, E. (2010) · International Journal of Computational Economics and Econometrics · doi:10.1504/ijcee.2010.037941 · Cited by 2 · see citing works

Frequentist model averaging in the generalized multinomial logit model

Zeng, T. (2022) · Computational Statistics · doi:10.1007/s00180-022-01306-4 · Cited by 2 · see citing works

Adjusting Band-Regression Estimators for Prediction: Shrinkage and Downweighting

Reschenhofer, E., & Chudý, M. (2015) · international journal of research in computer application & management · doi:10.12691/ijefm-3-3-3 · Cited by 2 · see citing works

Quantification of Modeling Uncertainty in Aeroelastic Design

Riley, M. E., Grandhi, R. V., & Kolonay, R. M. (2010) · AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (SDM) · doi:10.2514/6.2010-2679 · Cited by 2 · see citing works

Forecasting Financial Time Series Based on the Ensemble Method

Ivanyuk, V. A., Tsvirkun, A., Soloviev, V. I., Feklin, V., Sunchalina, A., & Kravchenko, O. V. (2022) · International Conference Management of Large-Scale System Development (MLSD) · doi:10.1109/mlsd55143.2022.9933994 · Cited by 2 · see citing works

Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations

Qiu, Y., & Zheng, Y. (2023) · Economic Modelling · doi:10.1016/j.econmod.2023.106349 · Cited by 2 · see citing works

Combining Predictive Densities Using Bayesian Filtering with Applications to US Economic DataPreprint

Billio, M., Casarin, R., Ravazzolo, F., & van Dijk, H. K. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.2118577 · Cited by 2 · see citing works

Combinación de pronósticos de la inflación en presencia de cambios estructurales

Melo‐Velandia, L. F., & Nuñez, H. (2004) · doi:10.32468/be.286 · Cited by 2 · see citing works

Model Averaging of Integer-Valued Autoregressive Model With CovariatesPreprint

Sun, J., Sun, Y., Zhang, X., & McCabe, B. P. M. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3846927 · Cited by 2 · see citing works

ESSAYS ON GROWTH ECONOMETRICS

Moral‐Benito, E. (2010) · Cited by 1 · see citing works

Una investigación científica acerca del progreso de métodos de ensamble basados en inteligencia computacional para predicción de series de tiempo económicas y financieras

Múñoz, R., & Fernanda, L. (2012) · Cited by 1 · see citing works

Are Negative Weights in Combining Forecasts So Bad?

Александрович, С. А. (2023) · Statistics and Economics · doi:10.21686/2500-3925-2023-4-4-11 · Cited by 1 · see citing works

Métodos de combinación de pronósticos: una aplicación a la inflación Colombiana

Castaño, E., & Melo‐Velandia, L. F. (1998) · doi:10.32468/be.109 · Cited by 1 · see citing works

Essays in Nonlinear Macroeconometrics: Fiscal Policy and Phillips Curve

Ferreira, D. (2014) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · Cited by 1 · see citing works

Estimating and Correcting the Effects of Model Selection Uncertainty

Tsague, G. L. E. N. (2006) · doi:10.53846/goediss-3679 · Cited by 1 · see citing works

Boosting Store Sales Through Machine Learning-Informed Promotional DecisionsPreprint

Qiu, Y., Wang, W., Xie, T., Yu, J., & Zhang, X. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4605803 · Cited by 1 · see citing works

Least Squares Model Averaging by Prediction CriterionPreprint

Xie, T., & Xie, T. (2012) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.274619 · Cited by 1 · see citing works

Combining generalized linear models

Chen, L. (2005) · doi:10.31274/rtd-180813-16444

Correction for Model Selection Bias Using a Modified Model Averaging Approach for Supervised Learning Methods Applied to EEG Experiments

Wouters, K., Abrahantes, J. C., Molenberghs, G., Geys, H., Ahnaou, A., Drinkenburg, W. H. I. M., & Bijnens, L. (2010) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543401003618744

Least Squares Model Averaging by Prediction Criterion (Job Market Paper)

Xie, T. (2012)

Bayesian modelling average on mixed attributed

Prabakaran, S., & Srinivasan, M. R. (2015)

Predicción de series temporales con redes neuronales: una aplicación a la inflación colombiana Forecasting Time Series with Neural Networks: An Application to the Colombian Inflation

Santana, J. C. (2006) · DOAJ (DOAJ: Directory of Open Access Journals)

Essays on Least Squares Model Averaging

Xie, T. (2013) · QSpace (Queen's University Library)

Towards Using Model Averaging To Construct Confidence Intervals In Logistic Regression Models

Uvarov, A. (2019) · Scholarship@Western (Western University)

A incorporação da incerteza devido à escolha de modelos na inferência estatística com aplicação em modelos de regressão linear

Candolo, C. (2019) · doi:10.11606/t.11.2019.tde-20191220-113413

Development of a combined method for predicting discrete time series with non-stability for forecasting military goods demand

Kubiv, S., & Balanyuk, Y. (2019) · Technology audit and production reserves · doi:10.15587/2312-8372.2019.188188

Forecast combinations in machine learningPreprint

Qiu, Y., Xie, T., & Yu, J. (2020) · RePEc: Research Papers in Economics

Robust numerical Bayesian unit root test for model uncertainty

Wu, X. (2015)

General algorithm for calculating the aggregated time series forecast

Moshkin, V., Yashin, D., Александрович, З. А., & Koval, A. (2021) · International Conference on Information Technology and Nanotechnology (ITNT) · doi:10.1109/itnt52450.2021.9649124

REFERENCES

(1986) · Elsevier eBooks · doi:10.1016/b978-0-12-295183-1.50017-0

Correcting sample selection bias with model averaging for consumer demand forecasting

Zhao, S., Xie, T., Ai, X., Yang, G., & Zhang, X. (2023) · Economic Modelling · doi:10.1016/j.econmod.2023.106275

O método de ponderação bayesiana de modelos para seleção de modelos

Zhangzhe, Z. (2023) · doi:10.11606/d.45.2023.tde-18042023-090238

Métodos no lineales en series económicas y/o financieras

de Guadalajara, U., Meléndez, C. A. B., Coronado, S., Cardona, C. J. F., Arreola, L. A. G., Gutiérrez, E. F., Pérez, R. H., Herrera, F. L., Matamoros, O. M., Hernández, C. I. M., et al. (2012) · Universidad de Guadalajara eBooks · doi:10.32870/9786074504873

Research on the volatility characteristics and evolutionary mechanism of the “Asian premium” for natural gas

Chai, J., Zhao, M., Zhang, X., Li, N., Zhang, Z., & Liu, Z. (2024) · Journal of Management Science and Engineering · doi:10.1016/j.jmse.2024.06.005

Model averaging: A shrinkage perspective

Peng, J. (2024) · Electronic Journal of Statistics · doi:10.1214/24-ejs2282

Quantitative Methods in FinancePreprint

Vansteenberghe, É. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5178205

Unsupervised Automated Configuration Selection for Ensemble PredictionPreprint

García-Aroca, C., Martínez-Mayoral, M., Morales, J., & Segura-Heras, J. V. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5533159

Composite Ordinal Forecasting in Horse Racing - An Optimization Approach

Tse, A. C. B., & Chan, C. (2012) · UNLV Gaming Research & Review Journal · doi:10.9741/2327-8455.1271

Validation des modèles statistiques tenant compte des variables dépendantes du temps en prévention primaire des maladies cérébrovasculaires

Kis, L. (2012) · doi:10.71781/15570

Quality Control and Statistical Methods.

Davies, O. L., & Schrock, E. M. (1951) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2980984 · Cited by 1 · see citing works

Statistical Methods in Quality Control.

Hill, I. D., & Cowden, D. J. (1957) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2343110

Statistical Quality Control Methods.

Bissell, D., & Burr, I. W. (1977) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344903 · Cited by 111 · see citing works

Quality Control.

Swan, A., & Edrick, H. L. (1955) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2342533

Essentials of Quality Control.

Wilkinson, R., Huitson, A., & Keen, J. (1966) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2343635 · Cited by 4 · see citing works