Nonlinear Conjugate Gradient Methods for Unconstrained Optimization, Andrei Neculai

Автор: Mishra Shashi Kant, Ram Bhagwat
Название: Introduction to Unconstrained Optimization with R
ISBN: 9811508968 ISBN-13(EAN): 9789811508967
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Поставка под заказ.

Описание: The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs.

Автор: Shashi Kant Mishra; Bhagwat Ram
Название: Introduction to Unconstrained Optimization with R
ISBN: 9811508933 ISBN-13(EAN): 9789811508936
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs.

Автор: Artur Lemonte
Название: The Gradient Test
ISBN: 012803596X ISBN-13(EAN): 9780128035962
Издательство: Elsevier Science
Рейтинг:
Цена: 8757.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

The Gradient Test: Another Likelihood-Based Test presents the latest on the gradient test, a large-sample test that was introduced in statistics literature by George R. Terrell in 2002. The test has been studied by several authors, is simply computed, and can be an interesting alternative to the classical large-sample tests, namely, the likelihood ratio (LR), Wald (W), and Rao score (S) tests.