Applied Statistics and Data Science: Proceedings of Statistics 2021 Canada, Selected Contributions

Author:   Yogendra P. Chaubey ,  Salim Lahmiri ,  Fassil Nebebe ,  Arusharka Sen
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
Volume:   375
ISBN:  

9783030861353


Pages:   159
Publication Date:   09 December 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Applied Statistics and Data Science: Proceedings of Statistics 2021 Canada, Selected Contributions


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Overview

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.

Full Product Details

Author:   Yogendra P. Chaubey ,  Salim Lahmiri ,  Fassil Nebebe ,  Arusharka Sen
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
Volume:   375
Weight:   0.279kg
ISBN:  

9783030861353


ISBN 10:   303086135
Pages:   159
Publication Date:   09 December 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of 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.

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Author Information

​Dr. Yogendra P. Chaubey is a Professor of Mathematics and Statistics at Concordia University. His research focus is in statistical methodology, mostly concentrated in the area of nonparametric smoothing.Dr. Fassil Nebebe is a Professor of Supply Chain and Business Technology Management at Concordia University. His research focuses on statistical methodology using resampling techniques, SEM, and predictive analytics. Dr. Arusharka Sen is an Associate Professor of Mathematics and Statistics at Concordia University. His research focuses on nonparametric function estimation and the analysis of censored data. Dr. Salim Lahmiri is an Assistant Professor of Supply Chain and Business Technology Management at Concordia University. He serves as associate editor for Expert Systems with Applications; Machine Learning with Applications; Chaos, Solitons & Fractals; Entropy; and Machine Learning & Knowledge Extraction. Dr. Lahmiri's research focuses on artificial intelligence, intelligent systems, data science, predictive analytics, and pattern recognition.

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