About Soumya Das Soumya Das Ph.D. Student, Statistics spatio-temporal statistics Soumya Das is a Ph.D. candidate in Statistics at King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Marc Genton. Education and Early Career M.sc. (2015-17) from Indian Institute of Technology Kanpur, Uttar Pradesh, India B.Sc. (2012-15) from Ramakrishna Mission Residential College (Autonomous), Narendrapur, Kolkata, West Bengal, India Research Interests Cyclostationary processes, Non-parametric analysis, Non-stationary models, Skewed distributions, Spatio-temporal statistics, Threshold models. Awards and Distinctions The General Proficiency Medal for Events Presented Events May 30 - Jun 5, 2021 Stationary and Cyclostationary Processes for Time Series and Spatio-Temporal Data Soumya Das, Ph.D. Student, Statistics Jun 1, 16:00 - 18:00 KAUST Due essentially to the difficulties associated with obtaining explicit forms of stationary marginal distributions of non-linear stationary processes, appropriate characterizations of such processes are worked upon little. After discussing an elaborate motivation behind this thesis and presenting preliminaries in Chapter 1, we characterize, in Chapter 2, the stationary marginal distributions of certain non-linear multivariate stationary processes. To do so, we show that the stationary marginal distributions of these processes belong to specific skew-distribution families, and for a given skew-distribution from the corresponding family, a process, with stationary marginal distribution identical to that given skew-distribution, can be found.
Stationary and Cyclostationary Processes for Time Series and Spatio-Temporal Data Soumya Das, Ph.D. Student, Statistics Jun 1, 16:00 - 18:00 KAUST Due essentially to the difficulties associated with obtaining explicit forms of stationary marginal distributions of non-linear stationary processes, appropriate characterizations of such processes are worked upon little. After discussing an elaborate motivation behind this thesis and presenting preliminaries in Chapter 1, we characterize, in Chapter 2, the stationary marginal distributions of certain non-linear multivariate stationary processes. To do so, we show that the stationary marginal distributions of these processes belong to specific skew-distribution families, and for a given skew-distribution from the corresponding family, a process, with stationary marginal distribution identical to that given skew-distribution, can be found.
Engage ORCID ShareClipboard Related Sites Statistics (STAT) Spatio-Temporal Statistics and Data Science (STSDS) Related Content Articles 1 Events 1
