Assistant Professor

Email:

Office: 331 Machray Hall

Telephone: 204-480-1074

Biography

Right after graduating from Taras Shevchenko University of Kiev with a Master's Degree in Mathematics, in September 2000 Yuliya V. Martsynyuk entered a graduate program in the School of Mathematics and Statistics of Carleton University in order to pursue her Ph.D. studies in Probability and Statistics under the supervision of Miklós Csörgő. [Professor Emeritus Miklós Csörgő, Distinguished Research Professor of Mathematics and Statistics at Carleton University, a Fellow of the Royal Society of Canada (F.R.S.C., Academy of Science), an External Member of the Hungarian Academy of Sciences, Fellow of the Institute of Mathematical Statistics, the 1996 recipient of the Gold Medal of the Statistical Society of Canada, is a renowned leader in creating and studying approximations of various data based stochastic processes by theoretically recognizable, usually Gaussian, ones. His research books and papers along these lines in more than 45 years now have had a major influence on several fields of the theory and applications of Probability, Statistics and Stochastic Processes.] Yuliya was admitted to the program with, and then continued to hold, a Carleton University International Student Scholarship for excellent entrance and maintained academic records (Fall 2000-Summer 2003) and a Faculty of Graduate Studies and Research Scholarship for excellent academic performance (Fall 2000-Summer 2005). In Winter 2001, she also obtained the David and Rachel Epstein Scholarship for excellence in graduate studies and research at Carleton University. In Fall 2005 Yuliya graduated from Carleton with a Ph.D. degree in Probability and Statistics, and was awarded a Carleton Senate Medal for Outstanding Academic Achievement.

Yuliya V. Martsynyuk's 2005 Ph.D. Thesis is titled “Invariance Principles via Studentization in Linear Structural and Functional Error-in-Variables Models”. It constitutes contributions to, and establishes an interplay between, two diverse fields of Statistics and Probability, namely, the field of asymptotic studies in regression models and that of self-normalized and Studentized partial sums and partial sums processes, and domains of attraction of univariate and multivariate normal laws. The results obtained in her Thesis and her further research in the above mentioned fields have resulted in several single-authored papers published in international refereed journals. Ever since being a graduate student, Yuliya has been presenting her research at various national and international conferences as an invited and contributing speaker.

After obtaining her Ph.D. degree, Yuliya decided to mainly concentrate on doing and publishing her research and thus became a Postdoctoral Fellow (PDF). She spent two of her four PDF years of Fall 2005-Summer 2009 at Carleton University, working under the supervision of Miklós Csörgő and Professor Barbara Szyszkowicz of the School of Mathematics and Statistics. In the period of July 2006-June 2008, she held an NSERC (the Natural Sciences and Engineering Research Council of Canada) Postdoctoral Fellowship at the University of Ottawa. During her PDF years in Ottawa, Yuliya was also a sessional lecturer in the School of Mathematics and Statistics of Carleton University and taught a wide variety of courses in Mathematics, Probability and Statistics.

In Fall 2008 Yuliya V. Martsynyuk applied for academic faculty positions at various Canadian universities. This, in turn, has led to her happily accepting, and presently holding, a full-time tenure track position at the rank of Assistant Professor in the Department of Statistics of the University of Manitoba, beginning July 1, 2009.

Comprehensive List of Research Interests

Error-in-variables models, regression models, reliability ratio and studies in error-in-variables models, infinite variance in regression and error-in-variables models, univariate and multivariate central limit theorems, functional central limit theorems, sup-norm approximations in probability in metric spaces, weak convergence in metric spaces, (vector) partial sums processes, self-normalization and Studentization, univariate and multivariate Student statistics, domain of attraction of the normal law, generalized domain of attraction of the multivariate normal law, asymptotic confidence intervals/regions, nonparametric change-point analysis, weak invariance principles in weighted sup-norms, Wiener and related Gaussian processes, weak and strong consistency, weakly dependent sequences of random variables.

Publications

Papers in Refereed Journals

1. Martsynyuk, Yu.V. (2009a). Functional asymptotic confidence intervals for the slope in linear error-in-variables models. Acta Mathematica Hungarica. 123 133-168
2. Martsynyuk, Yu.V. (2009b). Functional asymptotic confidence intervals for a common mean of independent random variables. The Electronic Journal of Statistics. 3 25-40
3. Martsynyuk, Yu.V. (2007a). New multivariate central limit theorems in linear structural and functional error-in-variables models. The Electronic Journal of Statistics. 1 347-380
4. Martsynyuk, Yu.V. (2007b). Central limit theorems in linear structural error-in-variables models with explanatory variables in the domain of attraction of the normal law. The Electronic Journal of Statistics. 1 195-222
5. Kukush, A.G. and Martsynyuk, Yu.V. (1999/2000). A criterion for the consistency of the least squares estimator for a functional linear model with errors in variables. Teoriya Imovirnostey ta Matematichna Statistika/Theory of Probability and Mathematical Statistics. 60 95-101/105-112 in Ukrainian/English
6. Kukush, A.G. and Martsynyuk, Yu.V. (1998). Consistency and inconsistency of the weighted least squares estimator in linear functional error-in-variables models.*Theory of Stochastic Processes*. 4(20) 172-179 Note: The Electronic Journal of Statistics (EJS) is sponsored by the Institute of Mathematical Statistics (IMS) and Bernoulli Society. It publishes research articles and short notes on theoretical, computational and applied statistics. To maintain the highest possible research standards, the EJS papers are refereed in the usual way, and at the same level as other IMS journals.

Note: Papers [3] and [4] as above are mentioned and discussed on p.216 of the research monograph de la Peña, V. H., Lai, T.L. and Shao, Q.-M., (2009), Self-Normalized Processes, Limit Theory and Statistical Applications, Springer, that was published in celebration of the centennial of one of the most famous seminal contributions of 20th century statistics, the paper by Student, The probable error of a mean, Biometrika, 6 (1908), 1-25. Moreover, [3] and [4] constitute a basis for parts of a Ph.D. thesis in preparation at the University of Ottawa (name withheld).

Paper Submitted to a Refereed Journal

#. Csörgő, M. and Martsynyuk, Yu.V. (2009). Studentized functional central limit theorems for least squares regression processes with infinite variance data. Submitted.

Note: The research in the papers listed above was supported by an NSERC Postdoctoral Fellowship of Yu.V. Martsynyuk at University of Ottawa, NSERC Individual Discovery Grants of M. Csörgő and B. Szyszkowicz at Carleton University, and a Carleton University Faculty of Graduate Studies and Research scholarship of Yu.V. Martsynyuk.

Technical Reports

1. Martsynyuk, Yu.V. (2008). Functional asymptotic confidence intervals for the slope in linear error-in-variables models. Technical Report Series of the Laboratory for Research in Statistics and Probability. 441-March 2008 Carleton University-University of Ottawa.
2. Martsynyuk, Yu.V. (2007). Invariance principles for self-randomized Student processes. Technical Report Series of the Laboratory for Research in Statistics and Probability. 438-March 2007 Carleton University-University of Ottawa.
3. Martsynyuk, Yu.V. (2006). Studentized and self-normalized central limit theorems in linear functional error-in-variables models.*Technical Report Series of the Laboratory for Research in Statistics and Probability*. 432- May 2006 Carleton University-University of Ottawa.
4. Martsynyuk, Yu.V. (2006). New central limit theorems via Studentization in linear structural error-in-variables models.*Technical Report Series of the Laboratory for Research in Statistics and Probability*. 428-February 2006 Carleton University-University of Ottawa.
5. Martsynyuk, Yu.V. (2004). Invariance principles via Studentization in linear structural error-in-variables models. Technical Report Series of the Laboratory for Research in Statistics and Probability. 406-October 2004 Carleton University-University of Ottawa.
6. Martsynyuk, Yu. V. (2001). Asymptotic behaviour of weighted least squares estimator in linear functional error-in-variables models.*Technical Report Series of the Laboratory for Research in Statistics and Probability*. 353-July 2001 Carleton University-University of Ottawa.

Thesis

• Martsynyuk, Yu.V. (2005). Invariance Principles via Studentization in Linear Structural and Functional Error-in-Variables Models. Ph.D. Thesis. Carleton University, Ottawa.

Awards, Fellowships, Scholarships

July 2006-June 2008 NSERC Postdoctoral Fellowship Fall 2006 The Graduate Institute Doctoral Prize, Carleton University-University of Ottawa Fall 2005 Senate Medal for Outstanding Academic Achievement, Carleton University Winter 2001 David and Rachel Epstein Scholarship (for excellence in graduate studies and research), Carleton University September 2000-August 2005 Faculty of Graduate Studies and Research Scholarship (for excellent academic performance), Carleton University September 2000-August 2003 International Student Scholarship (for excellent entrance and maintained academic records), Carleton University

Journal Refereeing Experience

The Journal of Multivariate Analysis, Statistics and Probability Letters, The Electronic Journal of Statistics

Invited Conference Talks

1. Csörgő, M. and Martsynyuk, Yu.V. A Glimpse of the First 100 Year Impact of “Student” (1908), The Probable Error of a Mean, Biometrika 6, 1-25. International Conference, Probability and Statistics with Applications, Dedicated to the 100th anniversary of the birthday of Bela Gyires. Faculty of Informatics, University of Debrecen, Hungary, June 8-13, 2009.
2. Martsynyuk, Yu.V. Invariance Principles and Functional Asymptotic Confidence Intervals for the Slope in Linear Structural and Functional Error-in-Variables Models. International Conference on Nonparametric Methods for Measurement Error Models and Related Topics. School of Mathematics and Statistics, Carleton University, May 3-5, 2009.
3. Martsynyuk, Yu.V. 38th Annual Meeting of the Statistical Society of Canada. Université Laval, Québec City, May 23-26, 2010.