Controllare lo stato dell'ordine

Entra a far parte di una comunità di amanti dei libri di tutto il mondo e ottieni numerosi vantaggi. Crea un account gratuito

Punto Poste 5.49 € Punto Poste 5.49 € Corriere DHL 6.99 € Corriere GLS 5.99 € Punto GLS 4.49 € Corriere Bartolini 4.49 € Punto Bartolini 3.49 €

Contatto

Come acquistare

Aiuto

Il mio account

▸ Vuoto :-(

Multivariate Reduced-Rank Regression: Theory, Methods and Applications

Name: Multivariate Reduced-Rank Regression: Theory, Methods and Applications
Brand: SPRINGER NATURE
SKU: 42522817
Price: 128.79 EUR
Availability: InStock
Author: Raja P. Velu
ISBN: 9781071627914

Raja P. Velu

Kun Chen

Lingua

Inglese

Libro In brossura

Codice Libristo: 42522817

Casa editrice SPRINGER NATURE, gennaio 2023

This book provides an account of multivariate reduced-rank regression, a tool of multivariate analys... Descrizione completa

Codice Libristo: 42522817

315 b

128.79 €

Magazzino esterno Inviamo tra 5-8 giorni

Fino a 30 giorni per il reso

I clienti hanno acquistato anche

Strategische Analyse Der Sekundaren Hypertoniepravention K Heidenberger

In brossura

55.29 €

BABADADA, magyar nyelv - Oromo, kepes szotar - kuusaa jechootaa mullataa Babadada Gmbh

In brossura

28.79 €

Jules au musée Magdalena

In brossura

7.29 €

From head to be toe (De la tête aux pieds) Hamels

In brossura

6.39 €

Thinking together - 6-28-03-7-27-05 Becker Libro

binding.

21.69 €

Tweelingzielen in Relaties: Hoe je je zielsverwant herkent, van hen houdt en weet wanneer het tijd is om los te laten - Inclusief eenvoudige en doeltr Louise Blumenberg

Adobe ePub DRM

0.89 €

Když je muž v lázních Irena Fuchsová

Libro

8.69 €

Verbale Aggression Silvia Bonacchi

Adobe ePub DRM

128.64 €

Puzzle Lokomotiva v bílém ruchu 1000 dílků Gioco/giocattolo

Puzzle

13.59 €

"Языковое мышление" и методы его исследования Г.П. Щедровицкий

Rigido

58.19 €

Il muto di Gallura Enrico Costa

Adobe ePub DRM

10.19 €

Cherche et trouve pour les tout-petits Beauregard

Leporello

17.19 €

Diccionario del español jurídico SANTIAGO MUÑOZ MACHADO

Rigido

104.79 €

Nutricion y Salud Guadalupe Rafael Torres Acosta

In brossura

204.09 €

Pokémon - Die ersten Abenteuer. Bd.2 Hidenori Kusaka

In brossura

8.09 €

Network Now A1 Starter Companion, m. Audio-CD Lynda Hübner

In brossura

24.39 €

Oeuvres de Moliere, Precedees d'Une Notice Sur Sa Vie Et Ses Ouvrages, Par M. Sainte-Beuve Moliere

In brossura

60.79 €

Quels Sont Les Fruits de la Sedition, de la Revolte Et de l'Usurpation ? Bouchard De La Poterie

In brossura

13.19 €

Adolf Hitler Xavier Leroy

In brossura

14.19 €

Antonio Perez Ludwig Scheyrer

In brossura

13.19 €

Nick Cave Mercy on Me Reinhard Kleist

Rigido

24.79 €

Vous qui passez dans l'ombre Niel

In brossura

16.99 €

Stávám se sám sebou Irvin D. Yalom

Rigido

3.59 €

Romancero Para Niños Y Jovenes (3ª Ed.) TERESA DE SANTOS

Rigido

10.49 €

This book provides an account of multivariate reduced-rank regression, a tool of multivariate analysis that enjoys a broad array of applications. In addition to a historical review of the topic, its connection to other widely used statistical methods, such as multivariate analysis of variance (MANOVA), discriminant analysis, principal components, canonical correlation analysis, and errors-in-variables models, is also discussed.

This new edition incorporates Big Data methodology and its applications, as well as high-dimensional reduced-rank regression, generalized reduced-rank regression with complex data, and sparse and low-rank regression methods. Each chapter contains developments of basic theoretical results, as well as details on computational procedures, illustrated with numerical examples drawn from disciplines such as biochemistry, genetics, marketing, and finance.

This book is designed for advanced students, practitioners, and researchers, who may deal withmoderate and high-dimensional multivariate data. Because regression is one of the most popular statistical methods, the multivariate regression analysis tools described should provide a natural way of looking at large (both cross-sectional and chronological) data sets. This book can be assigned in seminar-type courses taken by advanced graduate students in statistics, machine learning, econometrics, business, and engineering.