Design of Experiments in Nonlinear Models

Name: Design of Experiments in Nonlinear Models
Brand: Springer Nature
SKU: 9781461463634
Availability: InStock

Best Price:
Buy Design of Experiments in Nonlinear Models for $109.00 at @ Link.springer.com
No coupon is required — this is the standard retail price.

Set a price drop alert to never miss an offer.

1 Offer Price Range: $109.00 - $109.00

BEST PRICE

Single Product Purchase

$109.00

@ Link.springer.com BUY Now

Price Comparison

Seller	Contact Seller	List Price	On Sale	Shipping	Best Promo	Final Price	Volume Discount	Financing	Availability	Seller's Page
BEST PRICE 1 Product Purchase @ Link.springer.com		$109.00	$109.00			$109.00		See Site	In stock	Visit Store

Product Details

Brand

Springer Nature

Manufacturer

N/A

Part Number

GTIN

9781461463634

Condition

New

Product Description

Design of Experiments in Nonlinear Models: Asymptotic Normality, Optimality Criteria and Small-Sample Properties provides a comprehensivecoverage of the various aspects of experimental design for nonlinear models. The book contains original contributions to the theory of optimal experiments that will interest students and researchers in the field. Practitionners motivated by applications will find valuable tools to help them designing their experiments. The first three chapters expose theconnections between the asymptotic properties of estimators in parametric models and experimental design, with more emphasis than usual on some particular aspects like the estimation of a nonlinear function of the model parameters,models with heteroscedastic errors, etc. Classical optimality criteriabased on those asymptotic properties are then presented thoroughly in a special chapter. Three chapters are dedicated to specificissues raised by nonlinear models. The construction of designcriteria derived from non-asymptotic considerations (small-sample situation) is detailed. The connection between design and identifiability/estimability issues is investigated. Several approaches are presented to face the problem caused by the dependence of an optimal design on the value of the parameters to be estimated. A survey of algorithmic methods for the construction of optimal designs is provided.

Available Colors

N/A

Available Sizes

N/A