Statistical Inference for Models with Multivariate t-Distributed Errors 1st Edition

Author(s): A. K. Md. Ehsanes Saleh; Mohammad Arashi; S M M Tabatabaey
Publisher: Wiley-Blackwell
ISBN: 9781118854051
Edition: 1st Edition

$39,99

Delivery: This can be downloaded Immediately after purchasing.
Version: Only PDF Version.
Compatible Devices: Can be read on any device (Kindle, NOOK, Android/IOS devices, Windows, MAC)
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Description

Description

This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors: Includes a wide array of applications for the analysis of multivariate observations Emphasizes the development of linear statistical models with applications to engineering, the physical sciences, and mathematics Contains an up-to-date bibliography featuring the latest trends and advances in the field to provide a collective source for research on the topic Addresses linear regression models with non-normal errors with practical real-world examples Uniquely addresses regression models in Student’s t-distributed errors and t-models Supplemented with an Instructor’s Solutions Manual, which is available via written request by the Publisher

Statistical Inference for Models with Multivariate t-Distributed Errors 1st Edition

Author(s): A. Saleh
Publisher: John Wiley & Sons P&T
ISBN: 9781118854051
Edition: 1st Edition

$39,99

Delivery: This can be downloaded Immediately after purchasing.
Version: Only PDF Version.
Compatible Devices: Can be read on any device (Kindle, NOOK, Android/IOS devices, Windows, MAC)
Quality: High Quality. No missing contents. Printable

Recommended Software: Check here

Important: No Access Code

Description

Description

This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors: Includes a wide array of applications for the analysis of multivariate observations Emphasizes the development of linear statistical models with applications to engineering, the physical sciences, and mathematics Contains an up-to-date bibliography featuring the latest trends and advances in the field to provide a collective source for research on the topic Addresses linear regression models with non-normal errors with practical real-world examples Uniquely addresses regression models in Student’s t-distributed errors and t-models Supplemented with an Instructor’s Solutions Manual, which is available via written request by the Publisher