bayesian models

Ecological Models and Data in R - by Benjamin M Bolker (Hardcover)

Modelling Stochastic Uncertainties - (De Gruyter Textbook) by Mohammed Elmusrati (Paperback)

Quantum Computing and Quantum Machine Learning for Engineers and Developers - by Jesse Van Griensven Thé & Roydon Andrew Fraser & Jose Rosas-Bustos

Statistics by Simulation - by Carsten F Dormann & Aaron M Ellison

Time Series Analysis and Its Applications - (Springer Texts in Statistics) 5th Edition by Robert H Shumway & David S Stoffer (Hardcover)

Mathematical Models in Epidemiology - (Texts in Applied Mathematics) by Fred Brauer & Carlos Castillo-Chavez & Zhilan Feng (Hardcover)

Parametric Statistical Theory - (De Gruyter Textbook) by Johann Pfanzagl (Hardcover)

Statistical Distributions - 4th Edition by Catherine Forbes & Merran Evans & Nicholas Hastings & Brian Peacock (Paperback)

Machine Learning Design Patterns - by Valliappa Lakshmanan & Sara Robinson & Michael Munn (Paperback)

Statistics with Julia - (Springer the Data Sciences) by Yoni Nazarathy & Hayden Klok (Paperback)

Hybrid Random Fields - (Intelligent Systems Reference Library) by Antonino Freno & Edmondo Trentin (Hardcover)

Loss Data Analysis - (De Gruyter Stem) 2nd Edition by Henryk Gzyl & Silvia Mayoral & Erika Gomes-Gonçalves (Paperback)

Applied Reinforcement Learning - by Hadi Aghazadeh (Paperback)

Random Toeplitz Functionals and Their Applications - (Frontiers in Probability and the Statistical Sciences) by Mamikon S Ginovyan (Hardcover)

Let the Evidence Speak - by Alan Jessop (Paperback)

Quantization and Fast Inference - by Vivek Kalyanarangan (Paperback)

Probability and Statistics for Machine Learning - by Charu C Aggarwal (Hardcover)