Compartir
Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, With Applications (en Inglés)
Stasinopoulos Mikis D.; Kneib Thomas; Klein Nadja; Mayr Andreas; Heller Gillian Z. (Autor)
·
Cambridge University Press
· Tapa Dura
Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, With Applications (en Inglés) - Stasinopoulos Mikis D.; Kneib Thomas; Klein Nadja; Mayr Andreas; Heller Gillian Z.
$ 390.754
$ 601.159
Ahorras: $ 210.406
Elige la lista en la que quieres agregar tu producto o crea una nueva lista
✓ Producto agregado correctamente a la lista de deseos.
Ir a Mis Listas
Origen: Estados Unidos
(Costos de importación incluídos en el precio)
Se enviará desde nuestra bodega entre el
Miércoles 10 de Julio y el
Viernes 19 de Julio.
Lo recibirás en cualquier lugar de Colombia entre 1 y 5 días hábiles luego del envío.
Reseña del libro "Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, With Applications (en Inglés)"
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.