Efficient sequential designs with asymptotic second-order lower bound of Bayes risk for estimating product of means, Xing Xia

Resource Information

The instance Efficient sequential designs with asymptotic second-order lower bound of Bayes risk for estimating product of means, Xing Xia represents a material embodiment of a distinct intellectual or artistic creation found in University of Missouri-Kansas City Libraries. This resource is a combination of several types including: Instance, Electronic.

Label

Efficient sequential designs with asymptotic second-order lower bound of Bayes risk for estimating product of means, Xing Xia

Statement of responsibility

Xing Xia

Instantiates

• Efficient sequential designs with asymptotic second-order lower bound of Bayes risk for estimating product of means

Publication

• Kansas City, Missouri, University of Missouri-Kansas City, 2019

Copyright

• ©2019

Note

• "A dissertation in Mathematics and Telecommunication and Computer Networking."
• Advisors: Kamel Rekab and Deep Medhi,
• Vita

Antecedent source

not applicable

Bibliography note

Includes bibliographical references (pages 60-62)

Carrier category

online resource

Carrier category code

• cr

Carrier MARC source

rdacarrier

Color

black and white

Content category

text

Content type code

• txt

Content type MARC source

rdacontent

Contents

Introduction -- Conceptual framework -- Second-order efficiency for estimating product of 2 components in exponential family -- Second-order efficiency for estimating product of K components -- Conclusion

Control code

1135325087

Dimensions

unknown

Extent

1 online resource (63 pages)

File format

one file format

Form of item

online

Level of compression

mixed

Media category

computer

Media MARC source

rdamedia

Media type code

• c

Other physical details

illustrations.

Quality assurance targets

not applicable

Record ID

.b130815482

Specific material designation

remote

System control number

(OCoLC)1135325087

System details

• The full text of the dissertation is available as an Adobe Acrobat .pdf file; Adobe Acrobat Reader required to view the file
• Mode of access: World Wide Web