Name: Statistical Modelling With Quantile Functions (en Inglés)
Price: 252.04 USD
Availability: InStock
Author: Warren Gilchrist
ISBN: 9781584881742

portada Statistical Modelling With Quantile Functions (en Inglés)

Statistical Modelling With Quantile Functions (en Inglés)

Formato

Libro Físico

Editorial

Taylor & Francis Ltd

Autor

Warren Gilchrist

Año

2000

Idioma

Inglés

N° páginas

344

Encuadernación

Tapa Dura

ISBN13

9781584881742

N° edición

Categorías

Matemáticas aplicadas

Statistical Modelling With Quantile Functions (en Inglés)

Warren Gilchrist (Autor) · Taylor & Francis Ltd · Tapa Dura

Libro Nuevo Importado

Envío: 25 a 32 días háb.

$ 458.25$ 252.04

-45%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan más de 100 unidades

$ 252.04

Llega entre el 16 Sep y el 29 Sep a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Statistical Modelling With Quantile Functions (en Inglés)"

Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of statistical modelling that will be of value to anyone faced with analyzing data. Not intended to replace classical approaches but to supplement them, it will make some of the traditional topics easier and clearer, and help readers build and investigate models for their own practical statistical problems.