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Applied statistics and data sciencep...

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Applied statistics and data scienceproceedings of Statistics 2021 Canada, selected contributions /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applied statistics and data scienceedited by Yogendra P. Chaubey ... [et al.].
Reminder of title:	proceedings of Statistics 2021 Canada, selected contributions /
other author:	Chaubey, Yogendra P.
corporate name:
Published:	Cham :Springer International Publishing :2021.
Description:	ix, 159 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Mathematical statistics
Online resource:	https://doi.org/10.1007/978-3-030-86133-9
ISBN:	9783030861339$q(electronic bk.)

Applied statistics and data scienceproceedings of Statistics 2021 Canada, selected contributions /
Applied statistics and data scienceproceedings of Statistics 2021 Canada, selected contributions /[electronic resource] :edited by Yogendra P. Chaubey ... [et al.]. - Cham :Springer International Publishing :2021. - ix, 159 p. :ill., digital ;24 cm. - Springer proceedings in mathematics & statistics,v. 3752194-1017 ;. - Springer proceedings in mathematics & statistics ;v.19..

1. Minimum Profile Hellinger Distance Estimation for Semiparametric Simple Linear Regression Model -- 2. A Spatiotemporal Investigation of the Cod Stock in the Northern Gulf of St-Lawrence -- 3. Modeling Obesity Rate with Spatial Auto-correlation: A Case Study -- 4. Bayesian Inference for Inverse Gaussian Data with Emphasis on the Coefficient of Variation -- 5. Estimation and Testing of a Common Coefficient of Variation from Inverse Gaussian Distributions -- 6. A Markov Model of Polygenic Inheritance -- 7. Bayes Linear Emulation of Simulated Crop Yield.

This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021. Papers are contributed from established and emerging scholars, covering cutting-edge and contemporary innovative techniques in statistics and data science. Major areas of contribution include Bayesian statistics; computational statistics; data science; semi-parametric regression; and stochastic methods in biology, crop science, ecology and engineering. It will be a valuable edited collection for graduate students, researchers, and practitioners in a wide array of applied statistical and data science methods.

ISBN: 9783030861339$q(electronic bk.)

Standard No.: 10.1007/978-3-030-86133-9doiSubjects--Topical Terms:

182294
Mathematical statistics

LC Class. No.: QA276.A1 / A55 2021

Dewey Class. No.: 519.5

Applied statistics and data scienceproceedings of Statistics 2021 Canada, selected contributions /
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