Applied Statistics and Data Science: Proceedings of Statistics 2021 Canada, Selected Contributions: 375 (Springer Proceedings in Mathematics & Statistics)

Chaubey, Yogendra P. et al. (Eds.)

ISBN 10: 3030861325 / ISBN 13: 9783030861322

Editore: Springer, 2021

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privately owned book. as new from the publisher. -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. 176 pp. Englisch.

Codice articolo ABE-1691074470812

Dati bibliografici

• Titolo: Applied Statistics and Data Science: Proceedings of Statistics 2021 Canada, Selected Contributions: 375 (Springer Proceedings in Mathematics & Statistics)
• Editore: Springer
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 3030861325
• ISBN 13: 9783030861322
• Rilegatura: Hardcover
• Edizione: 1. Auflage
• Condizione: Wie neu

Descrizione articolo

Riassunto

<p>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.</p>

Informazioni sull?autore

<b>?</b><b>Dr. Yogendra P. Chaubey</b>&nbsp;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.<p><b>Dr. Fassil Nebebe</b>&nbsp;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.</p><p><b>Dr. Arusharka Sen</b>&nbsp;is an Associate Professor of Mathematics and Statistics at Concordia University. His research focuses on nonparametric function estimation and the analysis of censored data.</p><p><br></p><b>Dr. Salim Lahmiri</b>&nbsp;is an Assistant Professor of Supply Chain and Business Technology Management at Concordia University. He serves as associate editor for&nbsp;<i>Expert Systems with Applications</i>;&nbsp;<i>Machine Learning with Applications</i>;&nbsp;<i>Chaos, Solitons & Fractals</i>;&nbsp;<i>Entropy</i>; and&nbsp;<i>Machine Learning & Knowledge Extraction</i>. Dr. Lahmiri's research focuses on artificial intelligence, intelligent systems, data science, predictive analytics, and pattern recognition.