Generalized Additive Models

Main
Mathematics
Generalized Additive Models

Generalized Additive Models

T.J. Hastie, R.J. Tibshirani

5.0 / 3.0

Колко ви харесва тази книга?

Какво е качеството на файла?

Изтеглете книгата за оценка на качеството

Какво е качеството на изтеглените файлове?

Volume 43 of the series entitled, Monographs on Statistics and Applied Probability. Describes a new array of power tools for data analysis, based on nonparametric regression or smoothing techniques.

Категории:

Том:

43

Година:

1990

Издание:

1

Издателство:

Chapman and Hall/CRC Press

Език:

english

Страници:

175

ISBN 10:

0412343908

ISBN 13:

9780412343902

Серия:

Monographs On Statistics & Applied Probability

Файл:

PDF, 14.17 MB

IPFS:

,

english, 1990

Четете Онлайн

Преобразуването в се извършва

Преобразуването в е неуспешно

Може да се интересувате от

小乘单译经 — 佛说木槵经一卷

Alboukadel Kassambara — Practical Guide to Cluster Analysis in R. Unsupervised Machine Learning

Clements M.S. — Lung cancer rate predictions using generalized additive models

French J.L., Wand M.P. — Generalized additive models for cancer mapping with incomplete covariates

Zhang D., Lin X. — Hypothesis testing in semiparametric additive mixed models

Kassambara, Alboukadel — Machine Learning Essentials: Practical Guide in R

Boes, Duane C.;Graybill, Franklin A.;Mood, Alexander McFarlane — Introduction to the theory of statistics

Adrian W, Bowman Adelchi Azzalini — Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations

Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger — Analysis of Longitudinal Data, Second Edition

Christoph Molnar — Interpretable Machine Learning

Robert A. Rigby (Author); Mikis D. Stasinopoulos (Author); Gillian Z. Heller (Author); Fernanda De Bastiani (Author) — Distributions for Modeling Location, Scale, and Shape-Using GAMLSS in R

D.R. Cox (Author); P.J. Solomon (Author) — Components of Variance

James K. Lindsey — Applying Generalized Linear Models

Jiming Jiang — Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)

Carl De Boor — A Practical Guide to Splines (Revised Edition)

Seymour Geisser (auth.) — Predictive Inference: An Introduction

Bradley Efron, R.J. Tibshirani — An Introduction to the Bootstrap (Chapman & Hall CRC Monographs on Statistics & Applied Probability)

D. R. Cox, Walter L. Smith (auth.) — Queues

P.J. Green, Bernard. W. Silverman — Nonparametric Regression and Generalized Linear Models: A roughness penalty approach

P. McCullagh, John A. Nelder — Generalized linear models

T.J. Hastie; R.J. Tibshirani — Generalized Additive Models

M. P. Wand, M. C. Jones (auth.) — Kernel Smoothing

Neil Shephard (auth.), D. R. Cox, D. V. Hinkley, O. E. Barndorff-Nielsen (eds.) — Time Series Models: In econometrics, finance and other fields

Jinqing Fan; Gijbels, Irene — Local Polynomial Modelling and Its Applications: Monographs on Statistics and Applied Probability 66

N. W. Galwey — Introduction to Mixed Modelling: Beyond Regression and Analysis of Variance

Peter J. Huber, Elvezio M. Ronchetti — Robust statistics

Charles E. McCulloch, Shayle R. Searle — Generalized, Linear, and Mixed Models, Vol. 1

Norman L. Johnson, Adrienne W. Kemp, Samuel Kotz — Univariate Discrete Distributions

Hulin Wu, Jin-Ting Zhang — Nonparametric Regression Methods for Longitudinal Data Analysis: Mixed-Effects Modeling Approaches

David W. Scott — Multivariate density estimation: theory, practice, and visualization

David A. Belsley, Edwin Kuh, Roy E. Welsch — Regression Diagnostics - Identifying Influential Data and Sources of Collinearity

David W. Scott — Multivariate Density Estimation: Theory, Practice, and Visualization

K. Takezawa — Introduction to Nonparametric Regression

Douglas M. Bates, Donald G. Watts — Nonlinear regression analysis and its applications

David Ruppert, M. P. Wand, R. J. Carroll — Semiparametric regression

Roger Koenker — Quantile Regression

Bradley Efron — Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (Institute of Mathematical Statistics Monographs)

Roger Koenker — Quantile Regression

Randall L. Eubank — Nonparametric Regression and Spline Smoothing

Eugene V. Shikin, Alexander I. Plis — Handbook on splines for the user

Bradley Efron — The Jackknife, the Bootstrap, and Other Resampling Plans

Mikis D. Stasinopoulos, Robert A. Rigby, Gillian Z. Heller, Vlasios Voudouris, Fernanda De Bastiani — Flexible regression and smoothing : using GAMLSS in R

Най-често използвани термини