Results 31 to 40 of about 3,006,601 (299)
Statistical Models for Corporate Credit Risk Assessment – Rating Models
Acta Universitatis Lodziensis. Folia Oeconomica, 2016 Taking into consideration the weakness of the models based on discrimination function (Z-score) proposed by Altman within the conditions of polish economy some attempts were taken in the 90s to adjust these models to the reality of post-communist economy.
Aneta Ptak-Chmielewska
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SSRN Electronic Journal, 2016 44 pages; a trivial typo corrected, references updated; to appear in The Journal of Investment Strategies.
Kakushadze, Zura, Yu, Willie
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Acta Agriculturae Slovenica, 2001 Paper discusses the similarities and differences in predicting the full flowering of apple tree (cv. 'Bobovec'), pear tree (cv. 'Pastorjevka') and domestic plum tree. The study was conducted at University of Ljubljana.
Klemen BERGANT +2 more
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Train Performance Analysis Using Heterogeneous Statistical Models
Atmosphere, 2021 This study investigated the effect of a harsh winter climate on the performance of high-speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance to take time ...
Jianfeng Wang, Jun Yu
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Bradley-Terry models in R : the BradleyTerry2 package [PDF]
, 2012 This is a short overview of the R add-on package BradleyTerry2, which facilitates the specification and fitting of Bradley-Terry logit, probit or cauchit models to pair-comparison data.
Heather Turner +3 more
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Statistical physics of pairwise probability models
Frontiers in Computational Neuroscience, 2009 Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable
Yasser Roudi +4 more
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Parsimonious statistical learning models for low-flow estimation [PDF]
Hydrology and Earth System Sciences, 2022 Statistical learning methods offer a promising approach for low-flow regionalization. We examine seven statistical learning models (Lasso, linear, and nonlinear-model-based boosting, sparse partial least squares, principal component regression, random ...
J. Laimighofer, M. Melcher, G. Laaha
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Statistical models with uncertain error parameters
European Physical Journal C: Particles and Fields, 2019 In a statistical analysis in Particle Physics, nuisance parameters can be introduced to take into account various types of systematic uncertainties. The best estimate of such a parameter is often modeled as a Gaussian distributed variable with a given ...
Glen Cowan
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A machine learning approach to statistical shape models with applications to medical image analysis [PDF]
, 2010 Statistical shape models have become an indispensable tool for image analysis. The use of shape models is especially popular in computer vision and medical image analysis, where they were incorporated as a prior into a wide range of different algorithms.
Lüthi, Marcel
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, 2023 In the 1930s, Psychologists began developing Multiple-Factor Analysis to decompose multivariate data into a small number of interpretable factors without any a priori knowledge about those factors.
Yang, Dan +3 more
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