Bayesian Networks: With Examples in R (Chapman &...

Main
Computers - Computer Science
Bayesian Networks: With Examples in R...

Bayesian Networks: With Examples in R (Chapman & Hall/CRC Texts in Statistical Science)

Scutari, Marco, Denis, Jean-Baptiste

5.0 / 3.0

Jak bardzo podobała Ci się ta książka?

Jaka jest jakość pobranego pliku?

Pobierz książkę, aby ocenić jej jakość

Jaka jest jakość pobranych plików?

The book introduces Bayesian networks using simple yet meaningful examples. Discrete Bayesian networks are described first followed by Gaussian Bayesian networks and mixed networks. All steps in learning are illustrated with R code.

Kategorie:

Computers - Computer Science

Rok:

2021

Wydanie:

2

Wydawnictwo:

Chapman and Hall/CRC

Język:

english

Strony:

272

ISBN 10:

0367366517

ISBN 13:

9780367366513

Plik:

PDF, 18.67 MB

IPFS:

,

english, 2021

Czytaj Online

Trwa konwersja do

Konwersja do nie powiodła się

Możesz być zainteresowany

Roman Garnett — Bayesian Optimization

Sigrid Keydana — Deep Learning and Scientific Computing with R torch

Paula Moraga — Spatial Statistics for Data Science: Theory and Practice with R

Radhakrishnan Nagarajan, Marco Scutari;Sophie Lèbre — Bayesian networks in R: with applications in systems biology

Richard E. Neapolitan — Learning Bayesian networks

Pablo Inchausti — Statistical Modeling With R: A Dual Frequentist and Bayesian Approach for Life Scientists

B.E.A. Jacobs — Design of Slurry Transport Systems

Richard Mcelreath — Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science)

Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton — Modern Data Science with R (Chapman & Hall/CRC Texts in Statistical Science), 2nd Edition

Robert Shumway, David Stoffer — Time Series: A Data Analysis Approach Using R

Sujit Kumar Sahu — Bayesian Modelling of Spatio-Temporal Data with R

Lohr, Sharon L. — Sampling: Design and Analysis (Chapman & Hall/CRC Texts in Statistical Science), 3rd Edition

Marco Scutari; Jean-Baptiste Denis — Bayesian Networks: With Examples in R

Robert B. Gramacy (Author) — Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences

Darrin Speegle, Bryan Clair — Probability, Statistics, and Data: A Fresh Approach Using R

Jin Li, Taylor & Francis Group — Spatial Predictive Modelling with R

Coene, John — Javascript for R (Chapman & Hall/CRC The R Series)

Babette A. Brumback, Babette A. — Fundamentals of Causal Inference with R

Christophe Giraud — Introduction to High-Dimensional Statistics

Alan Agresti, Maria Kateri — Foundations of Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)

Martin, Osvaldo A., Kumar, Ravin, Lao, Junpeng — Bayesian Modeling and Computation in Python

Finn B. Jensen, Thomas D. Nielsen — Bayesian networks and decision graphs

Brian J. Reich, Sujit K. Ghosh — Bayesian Statistical Methods

Olivier Pourret, Patrick Naïm, Bruce Marcot — Bayesian Networks: A Practical Guide to Applications (Statistics in Practice)

Timo Koski, John Noble — Bayesian Networks: An Introduction (Wiley Series in Probability and Statistics)

Adnan Darwiche — Modeling and Reasoning with Bayesian Networks

Adnan Darwiche — Modeling and Reasoning with Bayesian Networks

Andrew B. Lawson — Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Olga Korosteleva — Stochastic Processes with R: An Introduction (Chapman & Hall/CRC Texts in Statistical Science)

Alicia A. Johnson, Miles Q. Ott, Mine Dogucu — Bayes Rules!: An Introduction to Applied Bayesian Modeling

Müller, Peter; Paulino, Carlos Daniel; Turkman, Maria Antónia Amaral — Computational Bayesian statistics : an introduction

Joseph B. Kadane — Principles of Uncertainty

Jim Albert; Jingchen Hu — Probability and Bayesian Modeling

Faraway, Julian James; Wang, Xiaofeng; Yue, Yu — Bayesian Regression Modeling with Inla

Kevin B. Korb, Ann E. Nicholson — Bayesian Artificial Intelligence

Paul Roback, Julie Legler — Beyond Multiple Linear Regression: Applied Generalized Linear Models And Multilevel Models in R

Nagarajan, Radhakrishnan, Scutari, Marco, Lèbre, Sophie — Bayesian Networks in R: with Applications in Systems Biology (Use R!, 48)

Jean-Michel Marin, Christian P. Robert — Bayesian Essentials with R

Jeffrey M. Stanton — Reasoning with Data: An Introduction to Traditional and Bayesian Statistics Using R

Sarah Depaoli — Bayesian Structural Equation Modeling

Rizzo, Maria L. — Statistical Computing with R, Second Edition (Chapman & Hall/CRC The R Series)

Denis, Jean-Baptiste; Scutari, Marco — Bayesian Networks: With Examples in R

Najbardziej popularne frazy

Powiązane listy książek