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 |