Least-squares Variance Component Estimation

Least-squares Variance Component Estimation
Author :
Publisher :
Total Pages : 228
Release :
ISBN-10 : UCSD:31822035691708
ISBN-13 :
Rating : 4/5 ( Downloads)

Book Synopsis Least-squares Variance Component Estimation by : AliReza Amiri-Simkooei

Download or read book Least-squares Variance Component Estimation written by AliReza Amiri-Simkooei and published by . This book was released on 2007 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Least-squares Variance Component Estimation Related Books

Least-squares Variance Component Estimation
Language: en
Pages: 228
Authors: AliReza Amiri-Simkooei
Categories: Geodesy
Type: BOOK - Published: 2007 - Publisher:

GET EBOOK

Variance Components
Language: en
Pages: 537
Authors: Shayle R. Searle
Categories: Mathematics
Type: BOOK - Published: 2009-09-25 - Publisher: John Wiley & Sons

GET EBOOK

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an ef
The Total Least Squares Problem
Language: en
Pages: 302
Authors: Sabine Van Huffel
Categories: Mathematics
Type: BOOK - Published: 1991-01-01 - Publisher: SIAM

GET EBOOK

This is the first book devoted entirely to total least squares. The authors give a unified presentation of the TLS problem. A description of its basic principle
VI Hotine-Marussi Symposium on Theoretical and Computational Geodesy
Language: en
Pages: 375
Authors: Peiliang Xu
Categories: Science
Type: BOOK - Published: 2008-02-27 - Publisher: Springer Science & Business Media

GET EBOOK

This volume of proceedings is a collection of refereed papers resulting from the VI Hotine-Marussi Symposium on Theoretical and Computational Geodesy. The paper
Applications of Linear and Nonlinear Models
Language: en
Pages: 1127
Authors: Erik W. Grafarend
Categories: Science
Type: BOOK - Published: 2022-10-01 - Publisher: Springer Nature

GET EBOOK

This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear an