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Title
Applied statistics and data science : proceedings of Statistics 2021 Canada, selected contributions / Yogendra P. Chaubey, Salim Lahmiri, Fassil Nebebe, Arusharka Sen, editors.
ISBN
9783030861339 (electronic bk.)
3030861333 (electronic bk.)
9783030861322 (print)
3030861325
Published
Cham : Springer, 2021.
Language
English
Description
1 online resource (ix, 159 pages) : illustrations.
Item Number
10.1007/978-3-030-86133-9 doi
Call Number
QA276.A1
Dewey Decimal Classification
519.5
Summary
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.
Note
Includes indexes.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 7, 2022).
Series
Springer proceedings in mathematics & statistics ; v.375. 2194-1017
Available in Other Form
Print version: 9783030861322
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.
