Applied Statistics and Data Science : Proceedings of Statistics 2021 Canada, Selected Contributions (Springer Proceedings in Mathematics & Statistics)

Chaubey, Yogendra P. (EDT)/ Lahmiri, Salim (EDT)/ Nebebe, Fassil (EDT)

Springer Nature Switzerland AG（2021/12発売）

• 製本 Hardcover:ハードカバー版／ページ数 159 p.
• 言語 ENG
• 商品コード 9783030861322

Full Description

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.

Contents

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.