Results 11 to 20 of about 2,028,100 (318)
Inverted Weibull Regression Models and Their Applications
, 2021 In this paper, we propose the classical and Bayesian regression models for use in conjunction with the inverted Weibull (IW) distribution; there are the inverted Weibull Regression model (IW-Reg) and inverted Weibull Bayesian regression model (IW-BReg ...
Sarah R. Al-Dawsari, Khalaf S. Sultan
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Prediction of Air Pollution Concentration Using Weather Data and Regression Models
Proceedings of the International Conference on Applied Innovations in IT, 2020 Air pollution is becoming a global environmental problem, in both developed and developing countries. It has greatly impacted the health and lives of millions of people, thus increasing mortality rates and pollution induced diseases reports.
Aleksandar Trenchevski +3 more
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Time-varying sparsity in dynamic regression models [PDF]
, 2014 A novel Bayesian method for inference in dynamic regression models is proposed where both the values of the regression coefficients and the importance of the variables are allowed to change over time.
Griffin, Jim E. +3 more
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Finite Mixtures of Generalized Linear Regression Models [PDF]
, 2007 Generalized linear models have become a standard technique in the statistical modelling toolbox for investigating relationships between variables.
Bettina Grün +3 more
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Dynamic Neural Regression Models [PDF]
, 2000 We consider sequential or online learning in dynamic neural regression models. By using a state space representation for the neural network' s parameter evolution in time we obtain approximations to the unknown posterior by either deriving posterior ...
Briegel, T., Tresp, V.
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Asymmetric Regression Models Bernoulli/LogProportional-Hazard Distribution
Revista Colombiana de Estadística, 2014 In this paper we introduce a kind of asymmetric distribution for non-negative data called log-proportional hazard distribution (LPHF). This new distribution is used to study an asymmetrical regression model for data with limited responses (censored ...
GUILLERMO MARTÍNEZ-FLÓREZ +1 more
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Bayesian Regularisation in Structured Additive Regression Models for Survival Data [PDF]
, 2008 During recent years, penalized likelihood approaches have attracted a lot of interest both in the area of semiparametric regression and for the regularization of high-dimensional regression models.
Konrath, Susanne +2 more
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Beneficium, 2019 The need to rethink, clarify and adjust the existing strategic planning document – Forecast of long-term socio-economic development of municipal formation city district «the City of Komsomolsk-on-Amur» for the period up to 2032 has determined the ...
Olesya V. Marchenko / Олеся В. Марченко +1 more
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Molecules, 2011 Logarithms of stability constants, log K1 and log β2, of the first transition series metal mono- and bis-complexes with any of four aliphatic amino acids (glycine, alanine, valine and leucine) decrease monotonously with third order valence connectivity ...
Ante Miličević +2 more
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On the Complexity of Logistic Regression Models [PDF]
Neural Computation, 2019 We investigate the complexity of logistic regression models, which is defined by counting the number of indistinguishable distributions that the model can represent (Balasubramanian, 1997 ). We find that the complexity of logistic models with binary inputs depends not only on the number of parameters but also on the distribution of inputs in a ...
Nicola Bulso +2 more
openaire +4 more sources