Generalized additive models for location, scale and shape: a distributional regression approach, with applications (Record no. 222757)

MARC details
000 -LEADER
fixed length control field 01930aam a2200229 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250115b2024 |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781009410069
Terms of availability £ 54.99
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.282
Item number S8G3
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Stasinopoulos, Mikis D.
9 (RLIN) 348394
245 1# - TITLE STATEMENT
Title Generalized additive models for location, scale and shape: a distributional regression approach, with applications
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Cambridge University Press
Date of publication, distribution, etc 2024
Place of publication, distribution, etc Cambridge
300 ## - PHYSICAL DESCRIPTION
Extent xx, 285p.
Other physical details Includes references and index
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Cambridge series in statistical and probabilistic mathematics
Number of part/section of a work 56
9 (RLIN) 428416
520 ## - SUMMARY, ETC.
Summary, etc An emerging field in statistics, distributional regression facilitates the modelling of the complete conditional distribution, rather than just the mean. This book introduces generalized additive models for location, scale and shape (GAMLSS) – one of the most important classes of distributional regression. Taking a broad perspective, the authors consider penalized likelihood inference, Bayesian inference, and boosting as potential ways of estimating models and illustrate their usage in complex applications. Written by the international team who developed GAMLSS, the text's focus on practical questions and problems sets it apart. Case studies demonstrate how researchers in statistics and other data-rich disciplines can use the model in their work, exploring examples ranging from fetal ultrasounds to social media performance metrics. The R code and data sets for the case studies are available on the book's companion website, allowing for replication and further study.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Regression analysis
General subdivision Mathematical models
9 (RLIN) 428417
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Theory of distributions (functional analysis)
9 (RLIN) 428418
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Kneib, Thomas
9 (RLIN) 318987
Relator term Co-author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Klein, Nadja
9 (RLIN) 428419
Relator term Co-author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Mayr, Andreas
9 (RLIN) 428420
Relator term Co-author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Heller, Gillian Z.
9 (RLIN) 428421
Relator term Co-author
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Item location Total Checkouts Total Renewals Full call number Barcode Checked out Date last seen Date last borrowed Cost, replacement price Koha item type
    Dewey Decimal Classification     Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library General Stacks 16/01/2025 8 4931.50 Rack 28-B / Slot 1405 (0 Floor, East Wing) 1 1 519.282 S8G3 207713 12/09/2025 17/01/2025 17/01/2025 6164.38 Books