Cambridge Series in Statistical and Probabilistic Mathematics
Séries de livres
par J. R. Norris
Dernier:
2020
Livre 1
Livre 2
Livre 3
Livre 4
Livre 5
Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers
par Thomas Leonard, John S. J. Hsu
Livre 6
Livre 7
Livre 8
Livre 9
Livre 10
Data Analysis and Graphics Using R: An Example-Based Approach
par John Maindonald, W. John Braun
Livre 11
Livre 12
Livre 14
Livre 15
Measure Theory and Filtering: Introduction and Applications
par Lakhdar Aggoun, Robert James Elliott
Livre 16
Livre 17
Livre 18
Livre 19
Livre 20
Livre 21
Livre 22
Livre 23
Applied Asymptotics: Case Studies in Small-Sample Statistics
par A. R. Brazzale, A. C. Davison, N. Reid
Applied Asymptotics: Cases Studies in Small-Sample Statistics. Cambridge Series in Statistical and Probabilistic Mathematics.
par A.R. Brazzale, A.C. Davison, N. Reid
Livre 24
Random Networks for Communication: From Statistical Physics to Information Systems
par Massimo Franceschetti, Ronald Meester
Livre 25
Livre 26
Livre 27
Model Selection and Model Averaging. Cambridge Series in Statistical and Probabilistic Mathematics.
par Gerda Claeskens, Nils Lid Hjort
Livre 28
Livre 29
From Finite Sample to Asymptotic Methods in Statistics
par Pranab K. Sen, Julio M. Singer, Antonio C. Pedroso de Lima
Livre 30
Livre 31
Livre 32
Livre 33
Livre 34
Livre 35
Exercises in Probability: A Guided Tour from Measure Theory to Random Processes, via Conditioning
par Loïc Chaumont, Marc Yor
Livre 36
Statistical Principles for the Design of Experiments: Applications to Real Experiments
par R. Mead, S. G. Gilmour, A. Mead
Statistical Principles for the Design of Experiments
par R. Mead, S.G. Gilmour, A. Mead
Livre 37
Livre 38
Nonparametric Estimation under Shape Constraints: Estimators, Algorithms and Asymptotics
par Piet Groeneboom, Geurt Jongbloed
Livre 39
Large Sample Covariance Matrices and High-Dimensional Data Analysis
par Jianfeng Yao, Zhidong Bai, Shurong Zheng
Livre 40
Mathematical Foundations of Infinite-Dimensional Statistical Models
par Evarist Giné, Richard Nickl, Evarist Ginae
Livre 41
Confidence, Likelihood, Probability: Statistical Inference with Confidence Distributions
par Tore Schweder, Nils Lid Hjort
Livre 42
Livre 43
Livre 44
Fundamentals of Nonparametric Bayesian Inference
par Subhashis Ghosal, Aad van der Vaart
Livre 45
Livre 46
Livre 47
Livre 48
Livre 50
Model-Based Clustering and Classification for Data Science: With Applications in R
par Charles Bouveyron, Gilles Celeux, T. Brendan Murphy
Livre 51
