Results 11 to 20 of about 14,251,254 (300)
New Journal of Physics, 2014 Standard tomographic analyses ignore model uncertainty. It is assumed that a given model generated the data and the task is to estimate the quantum state, or a subset of parameters within that model.
Christopher Ferrie
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Macroeconomic forecasting using model averaging [PDF]
, 2009 PhDRecently, there has been a broadening concern on forecasting techniques that are applied on large data sets, since economists in business and management want to deal with the great magnitude of information. In this analysis, the issue of forecasting
Verra, Christina
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Model Averaging in Viral Dynamic Models [PDF]
The AAPS Journal, 2020 The paucity of experimental data makes both inference and prediction particularly challenging in viral dynamic models. In the presence of several candidate models, a common strategy is model selection (MS), in which models are fitted to the data but only results obtained with the "best model" are presented.
Gonçalves, Antonio +3 more
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Mixture model averaging for clustering [PDF]
Advances in Data Analysis and Classification, 2014 In mixture model-based clustering applications, it is common to fit several models from a family and report clustering results from only the `best' one. In such circumstances, selection of this best model is achieved using a model selection criterion, most often the Bayesian information criterion.
Yuhong Wei, Paul D. McNicholas
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subtee: An R Package for Subgroup Treatment Effect Estimation in Clinical Trials
Journal of Statistical Software, 2021 The investigation of subgroups is an integral part of randomized clinical trials. Exploration of treatment effect heterogeneity is typically performed by covariate-adjusted analyses including treatment-by-covariate interactions.
Nicolas M. Ballarini +3 more
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BACE and BMA Variable Selection and Forecasting for UK Money Demand and Inflation with Gretl
Econometrics, 2020 In this paper, we apply Bayesian averaging of classical estimates (BACE) and Bayesian model averaging (BMA) as an automatic modeling procedures for two well-known macroeconometric models: UK demand for narrow money and long-term inflation.
Marcin Błażejowski +2 more
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Growth, convergence and public investment. A Bayesian model averaging approach [PDF]
, 2003 The aim of this study is twofold. First, the determinants of economic growth are studied among a wide set of potential variables for the Spanish provinces (NUTS3).
León González, Roberto +4 more
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A Comparison of Model Averaging Techniques to Predict the Spatial Distribution of Soil Properties
Remote Sensing, 2022 This study tested and evaluated a suite of nine individual base learners and seven model averaging techniques for predicting the spatial distribution of soil properties in central Iran.
Ruhollah Taghizadeh-Mehrjardi +5 more
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A survival mediation model with Bayesian model averaging [PDF]
Statistical Methods in Medical Research, 2021 Determining the extent to which a patient is benefiting from cancer therapy is challenging. Criteria for quantifying the extent of “tumor response” observed within a few cycles of treatment have been established for various types of solids as well as hematologic malignancies. These measures comprise the primary endpoints of phase II trials. Regulatory
Jie Zhou +4 more
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Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data
Mathematics, 2023 In the past few decades, model averaging has received extensive attention, and has been regarded as a feasible alternative to model selection. However, this work is mainly based on parametric model framework and complete dataset.
Guozhi Hu, Weihu Cheng, Jie Zeng
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