27 rows · PhD. Some new methods and models in functional data analysis (Abstract only available, The PhD program in Applied Statistics is a research intensive program designed for students who demand the depth in understanding of statistical methods to solve applied problems with innovation. The techniques and skills that students learn prepare them to become professionals in a broad range of statistics-driven fields, from academia to research-based industrial settings Prepare a dissertation representing an original contribution to existing knowledge of statistics, probability, or related area; Doctoral Candidate's Presentation: As a condition for Ph.D. candidacy, the student must make an oral presentation in an area of current research. The level of the presentation should demonstrate depth of knowledge, familiarity with research literature, and ability to write a Estimated Reading Time: 4 mins
Statistics Program - PhD in Statistics
Below is a list of the theses produced by graduate students in the Department of Statistics and Actuarial Science. Undergraduate Current Students Prospective Students Graduate Current Students Prospective Students Research Concentrations Seminars Resources Department Faculty Staff Statistical Consulting Graduate Students Sessionals Employment Forms Intranet News and Events Phd thesis applied statistics Elliott profiled in SFU's Scholarly Impact of the Week CANSSI Contact Us Directions.
Statistics and Actuarial Science Research Resources Graduate Theses, phd thesis applied statistics. Statistics and Actuarial Science. Semester Student Degree Thesis Supervisor Christina Nieuwoudt PhD Simulation and Statistical Methods for Family-Based Sequencing Studies J. Graham Louis Arsenault-Mahjoubi MSc On the Bayesian Estimation of Jump-Diffusion Models in Finance J. Bégin Cheng-Yu Sun PhD Factorial Designs under Baseline Parameterization and Space-filling Designs with Applications to Big Phd thesis applied statistics B.
Tang Xuefei Gloria Yang MSc Covariance-adjusted, phd thesis applied statistics, Sparse,Reduced-Rank Regression with Adjustment for Confounders B. McNeney Charith Karunarathna PhD Sequence Clustering for Genetic Mapping of Binary Traits J. Graham Lisa McQuarrie MSc Autoregressive Mixed Effects Models and an Application to Annual Income of Cancer Survivors R. Altman Yunwei Tu MSc Post-selection Inference R. Lockhart Nikola Surjanovic MSc An Efficient Approach to Pruning Regression Trees Using a Modified Bayesian Information Criterion T, phd thesis applied statistics.
Loughin Renny Doig MSc Efficient Bayesian parameter inference for COVID transmission models L. Wang Dylan Maciel MSc Systematic Comparison of Designs and Emulators for Computer Experiments Using a Library of Test Functions D.
Bingham Cherie Ng MSc A Flexible Group Benefits Framework for Pricing Deposit Rates J. Bégin James Thomson MSc Contextual Batting and Bowling in Limited Overs Cricket G. Perera Gabriel Phelan MSc New Perspectives on Non-negative Matrix Factorization for Grouped Topic Models D. Campbell Jacob Mortensen PhD Statistical Methods for Tracking Phd thesis applied statistics in Sports L.
Bornn Yi Xiong PhD Statistical Analysis of Event Times with Missing Origins Aided by Auxiliary Information, with Application to Wildfire Management J. Hu Shufei Ge PhD Statistical Machine Learning in Computational Genetics L. Wang Fei Mo MSc Understanding Jump Dynamics Using Liquidity Measures J.
Bégin Tainyu Guan PhD Some new methods and models in functional data analysis Abstract only available, publication of thesis postponed until 19th June, Cao Haiyang Jason Jiang MSc Understanding and Estimating Predictive Performance of Statistical Learning Methods based on Data Properties T. Loughin Nathan Sandholtz PhD Modeling human decision-making in spatial and temporal systems L. Bornn Zhiyang Gee Zhou PhD Supervised Basis Functions Applied to Functional Regression and Classification R.
Lockhart Matthew Reyers MSc Quarterback Evaluation in the National Football League T. Swartz Jie John Wang MSc Bayesian logistic regression with phd thesis applied statistics local bouncy particle sampler for COVID L. Wang Matt Berkowitz MSc A Bivariate Longitudinal Model for Psychometric Data R.
Altman Megan Kurz MSc Statistical analysis of multi-type recurrent events, with application in opioid use disorder studies J.
Hu Siyuan Chen MSc Approximate Marginal Likelihoods for Shrinkage Parameter Estimation in Penalized Logistic Regression Analysis of Case-Control Data B. McNeney Sihan Echo Cheng MSc An application of clustering methods to improving forecasting performances of mortality models C.
Tsai Barinder Thind MSc Functional Neural Networks for Scalar Prediction J. Cao Neil Faught MSc Assessing the performance of an open spatial mark recapture method on grizzly bear populations when age data is missing. Thompson Kanav Gupta MSc Optimal Investment and Consumption Strategy for a Retiree Under Stochastic Force of Mortality J. Bégin Dani Chu MSc Foul Accumulation in the NBA T, phd thesis applied statistics.
Projects and Theses From Previous Years. Undergraduate Overview Current Students Overview Advising Statistics Workshop Program Information Course Information Co-op Getting Involved Research Awards Accreditation EAL and Other Resources Prospective Students Overview Careers Degree Programs Admissions and Transferring Co-op Research Moving to SFU Graduate Overview Current Students Phd thesis applied statistics Program Information Course Information Teaching Assistant Positions Co-op Awards Defences EAL and Other Resources Prospective Students Overview Degree Programs Admissions Tuition and Financial Support Co-op Academic Resources Moving to SFU Research Overview Concentrations Overview Statistics Actuarial Science Data Science Seminars Resources Overview M.
and Ph. Defences Department Overview Faculty Staff Statistical Consulting Graduate Students Sessionals Employment Forms Intranet News and Events Overview Lloyd Elliott profiled in SFU's Scholarly Impact of the Week CANSSI Contact Us Overview Directions. This Site SFU. SFU Mail go SFU Canvas. Simulation and Statistical Methods for Family-Based Sequencing Studies, phd thesis applied statistics.
On the Bayesian Estimation of Jump-Diffusion Models in Finance. Factorial Designs under Baseline Parameterization and Space-filling Designs with Applications to Big Phd thesis applied statistics. Sequence Clustering for Genetic Mapping of Binary Traits.
Autoregressive Mixed Effects Models and an Application to Annual Income of Cancer Survivors. Post-selection Inference. An Efficient Approach to Pruning Regression Trees Using a Modified Bayesian Information Criterion. Efficient Bayesian parameter inference for COVID transmission models.
Systematic Comparison of Designs and Emulators for Computer Experiments Using a Library of Test Functions. A Flexible Group Benefits Framework for Pricing Deposit Rates. Contextual Batting and Bowling in Limited Overs Cricket.
New Perspectives on Non-negative Matrix Factorization for Grouped Topic Models. Statistical Methods for Tracking Data in Sports. Statistical Analysis of Event Times with Missing Origins Aided by Auxiliary Information, with Application to Wildfire Management.
Statistical Machine Learning in Computational Genetics. Understanding Jump Dynamics Using Liquidity Measures. Some new methods and models in functional data analysis Abstract only available, publication of thesis postponed until 19th June, Understanding and Estimating Predictive Performance of Statistical Learning Methods based on Data Properties.
Modeling human decision-making in spatial and temporal systems, phd thesis applied statistics. Supervised Basis Functions Applied to Functional Regression and Classification. Quarterback Evaluation in the National Football League. Bayesian logistic regression with the local bouncy particle sampler for COVID A Bivariate Longitudinal Model for Psychometric Data. Statistical analysis of multi-type recurrent events, with application in opioid use disorder studies.
Approximate Marginal Likelihoods for Shrinkage Parameter Estimation in Penalized Logistic Regression Analysis of Case-Control Data.
An application of clustering methods to improving forecasting performances of mortality models. Functional Neural Networks for Scalar Prediction. Assessing the performance of an open spatial mark recapture method on grizzly bear populations when age data is missing. Optimal Investment and Consumption Strategy for a Retiree Under Stochastic Force of Mortality.
Foul Accumulation in the NBA, phd thesis applied statistics.
Daniela Witten, PhD - The Role of Statistical Learning in Applied Statistics
, time: 37:18Dissertations & Theses | Department of Statistics
A Phd Thesis Applied Statistics secure network is the way we ensure that nobody breaks into our servers and finds your details or any of our essays writer’s essays. Our company is long established, so we are not going to take your money and run, which is what a lot of our competitors do/10() Gcse coursework on macbeth and phd thesis applied statistics. In considering each section you write, then you need to do business corporations have statistics applied phd thesis attempted to describe your results. Moving between micro-encounters among individual actors and policies sainsbury, c PhD Dissertation (Statistics): Modeling Multivariate Simulator Outputs with Applications to Prediction and Sequential Pareto Minimization Advisors: Thomas Santner & Angela Dean. Yanan Jia () PhD Dissertation (Statistics): Generalized Bilinear Mixed-Effects Models for Multi-Indexed Multivariate Data Advisor: Catherine Calder. Rong Lu ()
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