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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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GDP Forecasting: Machine Learning, Linear or Autoregression?
Frontiers in Artificial Intelligence, 2021 This paper compares the predictive power of different models to forecast the real U.S. GDP. Using quarterly data from 1976 to 2020, we find that the machine learning K-Nearest Neighbour (KNN) model captures the self-predictive ability of the U.S. GDP and
Giovanni Maccarrone +3 more
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Some Statistical Properties of Models of Transitory Earnings
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2021 The fact that most of the financial ratios are mean-reverting, is well known. Due to the importance of earnings forecast accuracy, relevant scientific literature in this area concentrates on transitory earnings.
Miroslava Vlčková, Tomáš Buus
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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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Improving risk prediction model quality in the critically ill: data linkage study
Health and Social Care Delivery Research, 2022 Background: A previous National Institute for Health and Care Research study [Harrison DA, Ferrando-Vivas P, Shahin J, Rowan KM. Ensuring comparisons of health-care providers are fair: development and validation of risk prediction models for critically ...
Paloma Ferrando-Vivas +17 more
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Statistical models of renewable energy intermittency [PDF]
E3S Web of Conferences, 2020 One of the big mitigating factors of intermittency is the smoothing effect of geographical distribution of variable renewable energy (VRE ) plants on the aggregate power output of VRE generation on a utility network.
Rakhmonov I U, Reymov K M
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Minimize the sum of the error boxes in the multi-linear regression model using the genetic algorithm [PDF]
مجلة التربية والعلم, 2018 Regression models are regarded as the most important ones used in statistical models in defining the relation among variables through the available data which can be applied to various sciences .
Hamsa Mohammed
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Health Technology Assessment, 2020 Background: Cost-effectiveness analysis using quality-adjusted life-years as the measure of health benefit is commonly used to aid decision-makers. Clinical studies often do not include preference-based measures that allow the calculation of quality ...
Mónica Hernández Alava +4 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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