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Statistical Models and Invariance [PDF]
The Annals of Mathematical Statistics, 1967 Brillinger [2] gives necessary and sufficient conditions for a model to be invariant under a Lie group of transformations. The problems that can be handled by his conditions are surveyed, and found effectively to be restricted to one-dimensional problems amendable to Lindley's [8] method and to problems connected with conflicts between Bayes' and ...
D. A. S. Fraser
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Bayesian statistics and modelling [PDF]
Nature Reviews Methods Primers, 2021 Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the ...
Mahlet G. Tadesse +12 more
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Statistical models of fracture [PDF]
Advances in Physics, 2006 Disorder and long-range interactions are two of the key components that make material failure an interesting playfield for the application of statistical mechanics. The cornerstone in this respect has been lattice models of the fracture in which a network of elastic beams, bonds or electrical fuses with random failure thresholds are subject to an ...
Mikko J. Alava +2 more
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Costs of Facade Systems Execution [PDF]
Archives of Civil Engineering, 2020 Cost estimation in the pre-design phase both for the contractor as well as the investor is an important aspect from the point of view of budget planning for a construction project.
Agnieszka Leśniak +2 more
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SSRN Electronic Journal, 2016 44 pages; a trivial typo corrected, references updated; to appear in The Journal of Investment Strategies.
Zura Kakushadze, Willie Yu
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Fisher’s significance test: A gentle introduction
GMS Medizinische Informatik, Biometrie und Epidemiologie, 2020 The p-value is often misunderstood and, for example, misinterpreted as a probability for the correctness of the null hypothesis. The aim of this article is to first explain the definition of the p-value.
Stang, Andreas, Kowall, Bernd
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ESC Heart Failure, 2020 This study aimed to review the performance of machine learning (ML) methods compared with conventional statistical models (CSMs) for predicting readmission and mortality in patients with heart failure (HF) and to present an approach to formally evaluate ...
Sheojung Shin +13 more
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Demographic and epidemiological characteristics of scorpion envenomation and daily forecasting of scorpion sting counts in Touggourt, Algeria [PDF]
Epidemiology and Health, 2020 OBJECTIVES This study was conducted to provide better insights into the demographic and epidemiological characteristics of scorpion envenomation in an endemic area in Algeria and to identify the model that best predicted daily scorpion sting counts ...
Kaouthar Boubekeur +2 more
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Machine Learning and Statistical Models to Predict Postpartum Hemorrhage.
Obstetrics and Gynecology, 2020 OBJECTIVE To predict a woman's risk of postpartum hemorrhage at labor admission using machine learning and statistical models. METHODS Predictive models were constructed and compared using data from 10 of 12 sites in the U.S.
M. P. Kartik K. Venkatesh +8 more
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Study of Abrasion of Rubber Materials by Experimental Design, Response Surface and Artificial Neural Network Modeling [PDF]
علوم و تکنولوژی پلیمر, 2015 Effect of different formulation ingredients on the abrasion behavior, crack growth and modulus of tire tread formulation was studied using two different case studies.
Mehdi Shiva +3 more
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