Torrent details for "[computer-internet] Statistical Modeling and Computation by Dirk P. Kroese PDF" Log in to bookmark
Controls:
Language:
EnglishTotal Size:
12.06 MB
Info Hash:
4258d46dccff8d8c149ab71162bc3dc81bdc4dcc
Added By:
Added:
25-01-2025 11:53
Views:
125
Health:
Seeds:
1
Leechers:
4
Completed:
0
xx
support my listings - book / audiobook requests form - thank you
https://linktr.ee/libraryaisle42
xx
This book, Statistical Modeling and Computation, provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of mathematical statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications.
The 2nd edition changes the programming language used in the text from MATLAB to Julia. For all examples with computing components, the authors provide data sets and their own Julia codes. The new edition features numerous full color graphics to illustrate the concepts discussed in the text, and adds three entirely new chapters on a variety of popular topics, including:
Regularization and the Lasso regression
Bayesian shrinkage methods
Nonparametric statistical tests
Splines and the Gaussian process regression
xx
support my listings - book / audiobook requests form - thank you
https://linktr.ee/libraryaisle42
xx
This book, Statistical Modeling and Computation, provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of mathematical statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications.
The 2nd edition changes the programming language used in the text from MATLAB to Julia. For all examples with computing components, the authors provide data sets and their own Julia codes. The new edition features numerous full color graphics to illustrate the concepts discussed in the text, and adds three entirely new chapters on a variety of popular topics, including:
Regularization and the Lasso regression
Bayesian shrinkage methods
Nonparametric statistical tests
Splines and the Gaussian process regression
xx