Fundraising September 15, 2024 – October 1, 2024 About fundraising

Generalized Additive Models

Main
Mathematics
Generalized Additive Models

Generalized Additive Models

T.J. Hastie, R.J. Tibshirani

5.0 / 3.0

How much do you like this book?

What’s the quality of the file?

Download the book for quality assessment

What’s the quality of the downloaded files?

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.

Categories:

Volume:

43

Year:

1990

Edition:

1

Publisher:

Chapman and Hall/CRC Press

Language:

english

Pages:

175

ISBN 10:

0412343908

ISBN 13:

9780412343902

Series:

Monographs On Statistics & Applied Probability

File:

PDF, 14.17 MB

IPFS:

,

english, 1990

Read Online

Conversion to is in progress

Conversion to is failed

You may be interested in

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

Most frequently terms