An edition of Bayesian Analysis with R for Drug Development (2019)

Bayesian Analysis with R for Drug Development

Concepts, Algorithms, and Case Studies

by and

Cover of: Bayesian Analysis with R for Drug Development by Harry Yang, Steven Novick, Harry Yang, Steven Novick
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Last edited by ImportBot
April 9, 2023 | History
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An edition of Bayesian Analysis with R for Drug Development (2019)

Bayesian Analysis with R for Drug Development

Concepts, Algorithms, and Case Studies

by and

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Publish Date
Publisher
Taylor & Francis Group, Chapman and Hall/CRC
Language
English
Pages
310

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Subjects

Drugs, Clinical trials, Bayesian statistical decision theory, Programming languages (electronic computers), Drug development, Biopharmaceutics, R (Computer program language), MATHEMATICS / Probability & Statistics / General, MEDICAL / Pharmacy, MEDICAL / Biostatistics, Arzneimittelentwicklung, Bayes-Entscheidungstheorie, Klinisches Experiment, R
Edition Availability
Cover of: Bayesian Analysis with R for Drug Development
Bayesian Analysis with R for Drug Development
2021, Taylor & Francis Group
in English
Cover of: Bayesian Analysis with R for Drug Development
Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies
2019, Taylor & Francis Group
in English
Cover of: Bayesian Analysis with R for Drug Development
Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies
2019, Taylor & Francis Group
in English
Cover of: Bayesian Analysis with R for Drug Development
Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies
2019, Taylor & Francis Group
in English
Cover of: Bayesian Analysis with R for Drug Development
Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies
2019, Taylor & Francis Group
in English
Cover of: Bayesian Analysis with R for Drug Development
Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies
2019, Taylor & Francis Group, Chapman and Hall/CRC
in English

Add another edition?

Book Details

Classifications

Library of Congress
RM301.25.Y36 2019

The Physical Object

Pagination
310
Number of pages
310
Weight
0.827

ID Numbers

Open Library
OL34647767M
ISBN 13
9781138295872

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Download catalog record: RDF / JSON / OPDS | Wikipedia citation
April 9, 2023 Edited by ImportBot import existing book
October 6, 2021 Created by ImportBot Imported from Better World Books record