Local Sensitivity of Failure Probability through Polynomial Regression and Importance Sampling
Mathematics, 2023 Evaluating the failure probability of a system is essential in order to assess its reliability. This probability may significantly depend on deterministic parameters such as distribution parameters or design parameters.
Marie Chiron +2 more
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Bayesian probability updates using sampling/importance resampling: Applications in nuclear theory
Frontiers in Physics, 2022 We review an established Bayesian sampling method called sampling/importance resampling and highlight situations in nuclear theory when it can be particularly useful.
Weiguang Jiang, Christian Forssén
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EDITORIAL – A REVIEW OF THE METHODOLOGICAL MISCONCEPTIONS AND GUIDELINES RELATED TO THE APPLICATION OF STRUCTURAL EQUATION MODELING: A MALAYSIAN SCENARIO [PDF]
Journal of Applied Structural Equation Modeling, 2017 Although structural equation modeling (SEM) is a powerful statistical technique, understanding its methodological assumptions before data analyses is essential to attaining more robust results.
Mumtaz Ali Memon +4 more
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Essay: Sunday shopping - The case of three surveys
Survey Research Methods, 2015 There is a growing discussion about the use of non-probability sampling in survey research. Probability sampling is the preferred method of sample selection, but practical problems like reduced data collection budgets, increasing nonresponse rates, and ...
Jelke Bethlehem
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On accuracy of PDF divergence estimators and their applicability to representative data sampling [PDF]
, 2011 Generalisation error estimation is an important issue in machine learning. Cross-validation traditionally used for this purpose requires building multiple models and repeating the whole procedure many times in order to produce reliable error estimates ...
Musial, Katarzyna +6 more
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Deep Hash Remote Sensing Image Retrieval with Hard Probability Sampling
Remote Sensing, 2020 As satellite observation technology improves, the number of remote sensing images significantly and rapidly increases. Therefore, a growing number of studies are focusing on remote sensing image retrieval. However, having a large number of remote sensing
Xue Shan +4 more
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Probabilistic sampling strategy as a means of improving quality of price indices
Croatian Review of Economic, Business and Social Statistics, 2018 In spite of theoretical inferiority, a large majority of statistical institutes use non-probabilistic sampling techniques in price surveys. The main disadvantage of non-probabilistic sample design is that the risk of biased results is increased ...
Seljak Rudi +3 more
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Remote Sensing, 2013 This paper complies with the Quality Assurance Framework for Earth Observation (QA4EO) international guidelines to provide a metrological/statistically-based quality assessment of the Spectral Classification of surface reflectance signatures (SPECL ...
Andrea Baraldi +2 more
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Against All Odds: On the Robustness of Probability Samples Against Decreases in Response Rates
Survey Research MethodsResponses rates in surveys with probability samples have decreased in the last decades, but has this decrease caused a decline in sample quality? Our paper addresses this question with an analysis of methodological data describing 776 surveys from four ...
Piotr Jabkowski +2 more
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Empirical likelihood inference for the Rao-Hartley-Cochran sampling design
, 2016 The Hartley-Rao-Cochran sampling design is an unequal probability sampling design which can be used to select samples from finite populations. We propose to adjust the empirical likelihood approach for the Hartley-Rao-Cochran sampling design.
Yves G. Berger, Berger, Yves G.
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