"Posterior Predictive Model Checking and Proportion of Explained Variance"

entries per page

Filter:

Showing 1 to 20 of 100 entries

Book	Author(s)	Year	Publisher
Model checking /	Clarke, Edmund M.,		The MIT Press
Model checking /	Clarke, Edmund M.,; Grumberg, Orna.; Peled, Doron A.,	c1999.	MIT Press,
Model checking /	Clarke, Edmund M.,; Grumberg, Orna,; Peled, Doron A.,	©1999.	MIT Press,
Handbook of Model Checking	Edmund M. Clarke; Thomas A. Henzinger; Helmut Veith; Roderick Bloem	1st ed. 2018	Springer International Publishing
Principles of model checking /	Baier, Christel.; Katoen, Joost-Pieter.	[2008?]	The MIT Press,
Symbolic Model Checking	Kenneth L. McMillan	1993	Springer US
Posterior and Predictive Densities for Simultaneous Equation Models	J.-F. Richard	1973	Springer Berlin Heidelberg
Posterior and predictive densities for simultaneous equation models	Jean François Richard	1973	Springer-Verlag
Model Predictive Control	Carlos Bordons Alba	1999	Springer London
Model Predictive Control	Eduardo F. Camacho; Carlos Bordons Alba	2nd ed. 2004	Springer London
Model Predictive Control	Tao ZHENG	2010	Sciyo
Handbook of Model Predictive Control	Saša V. Raković; William S. Levine	1st ed. 2019	Springer International Publishing
Model Predictive Control of Microgrids	Carlos Bordons; Félix Garcia-Torres; Miguel A. Ridao	1st ed. 2020	Springer International Publishing
Nonlinear Model Predictive Control	Frank Allgöwer; Alex Zheng	2000	Birkhäuser Basel
Advanced Model Predictive Control	T. Zheng	2011	Intech
Model Predictive Control of Wastewater Systems	Carlos Ocampo-Martinez	2010	Springer London
Model Checking Quantum Systems: Principles and Algorithms	Mingsheng Ying; Yuan Feng	2021-02	Cambridge University Press
Practical Design and Application of Model Predictive Control	Nassim Khaled and Bibin Pattel	2018	Butterworth-Heinemann
Nonlinear Model Predictive Control: Theory and Algorithms	Lars Grüne; Jürgen Pannek	2011	Springer London
Nonlinear Model Predictive Control: Theory and Algorithms	Lars Grüne; Jürgen Pannek	2nd ed. 2017	Springer International Publishing
Boook	Author(s)	Year	Publisher

Showing 1 to 20 of 100 entries

entries per page

Filter:

Showing 1 to 20 of 100 entries

Chapter	Author(s)	Book	Book Authors	Year	Publisher
Posterior Predictive Model Checking and Proportion of Explained Variance	Fränzi Korner-Nievergelt; Tobias Roth; Stefanie von Felten; Jérôme Guélat; Bettina Almasi; Pius Korner-Nievergelt	Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan	Franzi Korner-Nievergelt; Stefanie von Felten; Tobias Roth; Bettina Almasi; Jérôme Guélat and Pius Korner-Nievergelt	2015	Academic Press
1121 Posterior Predictive Model Checking		Bayesian Structural Equation Modeling	Sarah Depaoli	2021	Guilford Press
Proportion ofÂ variance explained		SPSS for psychologists	Richard Kemp; Rosemary Snelgar; Nicola Brace; Virginia Harrison	2021	Red Globe Press
The Proportion of Variance Explained		An Introduction to Statistical Learning with Applications in R	Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani	2014	Springer
Proportion of variance explained at each level		Data Analysis Using Regression and Multilevel/Hierarchical Models	Andrew Gelman, Jennifer Hill	2007	Cambridge University Press
Structural Model – Overall Variance Explained		Technology Acceptance in Education: Research and Issues	Timothy Teo	2011	Sense Publishers
Explained variance		Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling	Tom A B Snijders; Roel J Bosker	December 2011	SAGE Publications Ltd
Explained variance		Machine Learning Algorithms	Giuseppe Bonaccorso	2018	Packt Publishing
The Predictive Distribution and Model Checking		Bayesian Modeling Using WinBUGS	Ioannis Ntzoufras	2009	John Wiley & Sons
Total and explained variance		Python Machine Learning Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2	by Sebastian Raschka (Author), Vahid Mirjalili (Author)	2019	Packt
Total and explained variance		Python Machine Learning - Second Edition	Raschka, Sebastian; Mirjalili, Vahid	2017	Packt Publishing
Total and explained variance		MACHINE LEARNING WITH PYTORCH AND SCIKIT-LEARN: develop machine learning and deep learning. . . models with scikit-learn and pytorch.	SEBASTIAN LIU YUXI (HAYDEN) MIRJALILI VAHID RASCHKA	2022	PACKT PUBLISHING LIMITED
Total and explained variance		Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition	Raschka, Sebastian; Mirjalili, Vahid	2019	Packt Publishing
Total and explained variance		Python: Real-World Data Science	Dusty Phillips, Fabrizio Romano, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka	2016	Packt Publishing Limited
Total and explained variance		Python: Real-World Data Science: A course in four modules	Dusty Phillips, Fabrizio Romano, Phuong Vo.T.H, Martin Czygan, Robert Layton	2016	Packt Publishing
43â€¦Model Checking with Summary Statistics from the Posterior Predictive Distribution		Bayesian inference for probabilistic risk assessment	Kelly D., Smith C	2011	Springer
Explained Variance Ratio		Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow - Concepts, Tools, and Techniques to Build Intelligent Systems, 2nd Edition	Aurélien Géron	2019	O'Reilly
223 Explained Variance		Process Dynamics and Control Modeling for Control and Prediction	Brian Roffel, Ben Betlem	2007	Wiley
Explained Variance Ratio		Hands-On Machine Learning with Scikit-Learn and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems	Géron, Aurélien	2017	O'Reilly Media
Explained Variance Ratio		Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow	Aurelien Geron	2019	O’reilly
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

"Posterior Predictive Model Checking and Proportion of Explained Variance" - similar Books and Chapters