Probability: With Applications And R
Model-Based Clustering and Classification for Data Science: With Applications in R eBooks & eLearning
Posted by hill0 at May 21, 2020
Model-Based Clustering and Classification for Data Science: With Applications in R
by Charles Bouveyron
English | 2019 | ISBN: 110849420X | 447 Pages | PDF | 41 MB
by Charles Bouveyron
English | 2019 | ISBN: 110849420X | 447 Pages | PDF | 41 MB
Model-Based Clustering and Classification for Data Science: With Applications in R eBooks & eLearning
Posted by hill0 at Nov. 12, 2019
Model-Based Clustering and Classification for Data Science: With Applications in R
(Cambridge Series in Statistical and Probabilistic Mathematics Book 50)
by Charles Bouveyron
English | 2019 | ISBN: 110849420X | 446 Pages | PDF | 62 MB
(Cambridge Series in Statistical and Probabilistic Mathematics Book 50)
by Charles Bouveyron
English | 2019 | ISBN: 110849420X | 446 Pages | PDF | 62 MB
The Statistical Analysis of Doubly Truncated Data : With Applications in R eBooks & eLearning
Posted by yoyoloit at Nov. 10, 2021
The Statistical Analysis of Doubly Truncated Data
by de Uña-Álvarez, Jacobo;Crujeiras, Rosa M.;Moreira, Carla;
English | 2022 | ISBN: 1119951372 , 978-1119951377 | 195 pages | True PDF | 3.5 MB
by de Uña-Álvarez, Jacobo;Crujeiras, Rosa M.;Moreira, Carla;
English | 2022 | ISBN: 1119951372 , 978-1119951377 | 195 pages | True PDF | 3.5 MB
Probability with R: An Introduction with Computer Science Applications eBooks & eLearning
Posted by roxul at Oct. 1, 2016
Jane Horgan, "Probability with R: An Introduction with Computer Science Applications"
English | ISBN: 0470280735 | 2008 | 416 pages | PDF | 11 MB
English | ISBN: 0470280735 | 2008 | 416 pages | PDF | 11 MB
Probability with R: An Introduction with Computer Science Applications eBooks & eLearning
Posted by insetes at Sept. 30, 2021
Probability with R: An Introduction with Computer Science Applications By Jane Horgan
2008 | 416 Pages | ISBN: 0470280735 | PDF | 12 MB
2008 | 416 Pages | ISBN: 0470280735 | PDF | 12 MB
Probability with R: An Introduction with Computer Science Applications, 2nd Edition eBooks & eLearning
Posted by viserion at Jan. 3, 2020
Jane M. Horgan, "Probability with R: An Introduction with Computer Science Applications, 2nd Edition"
ISBN: 1119536944 | 2020 | PDF | 496 pages | 13 MB
Probability and Mathematical Statistics: Theory, Applications, and Practice in R eBooks & eLearning
Posted by arundhati at March 19, 2020
Mary C. Meyer, "Probability and Mathematical Statistics: Theory, Applications, and Practice in R"
English | ISBN: 1611975778 | 2019 | pages | PDF | 19 MB
English | ISBN: 1611975778 | 2019 | pages | PDF | 19 MB
Probability With R For Statistics And Data Science eBooks & eLearning
Posted by ELK1nG at Sept. 25, 2023
Probability With R For Statistics And Data Science
Published 9/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.40 GB | Duration: 4h 48m
Published 9/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.40 GB | Duration: 4h 48m
Master common probability distributions using the R programming language - with 100+ coding problems included.
Probability and Statistics for Engineering and the Sciences with Modeling using R eBooks & eLearning
Posted by yoyoloit at Dec. 2, 2022
Probability and Statistics for Engineering and the Sciences with Modeling using R
by William P. Fox
English | 2022 | ISBN: 1032330473 | 429 pages | True PDF | 12.14 MB
by William P. Fox
English | 2022 | ISBN: 1032330473 | 429 pages | True PDF | 12.14 MB
Factorization Calculus and Geometric Probability (Encyclopedia of Mathematics and its Applications) by R. V. Ambartzumian eBooks & eLearning
Posted by BUGSY at May 1, 2015
Factorization Calculus and Geometric Probability (Encyclopedia of Mathematics and its Applications, Vol. 33) by R. V. Ambartzumian
English | Nov 6, 2008 | ISBN: 0521345359, 0521089786 | 299 Pages | PDF | 11 MB
English | Nov 6, 2008 | ISBN: 0521345359, 0521089786 | 299 Pages | PDF | 11 MB
The classical subjects of geometric probability and integral geometry, and the more modern one of stochastic geometry, are developed here in a novel way to provide a framework in which they can be studied. The author focuses on factorization properties of measures and probabilities implied by the assumption of their invariance with respect to a group, in order to investigate nontrivial factors.