Shemyakin, Arkady portrait

Shemyakin, Arkady

Professor
Degree
Ph.D., Russian Academy of Sciences-Siberia
Office
OSS 221
Phone
(651) 962-5522
Toll Free
(800) 328-6819, Ext. 2-5522
Fax
651-962-5670
Mail
OSS 201

Arkady Shemyakin did his graduate study at Novosibirsk State University and post-graduate study at the Sobolev Institute of Mathematics in Novosibirsk, Russia. His main research interests lie in the field of Bayesian Statistics, non-informative priors, and copula analysis with the emphasis on applications to Insurance and Finance.

Dr. Shemyakin has taught full-time at Novosibirsk State University and as a visiting professor at several schools including Astrakhan State University in Russia, University of Minnesota and Heriot-Watt University in Edinburgh, UK.

Arkady is the current President of American Siberian Education Foundation and the past President of the Twin Cities chapter of American Statistical Association. He serves on the editorial boards and as a reviewer for several statistical journals. Besides that, he tries to spend as much time as possible playing chess, tennis, and skiing.

Fall 2018 Courses

Fall 2018 Courses
Course - Section Title Days Time Location
ACSC 489 - 01 Actuarial Science Topics - T - - - - - 1715 - 2015 OSS 214

Days of Week:

- T - - - - -

Time of Day:

1715 - 2015

Location:

OSS 214

Course Registration Number:

42199 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Arkady Shemyakin, Kathryn E. Dederichs

The subject matter of these courses will vary from year to year, but will not duplicate existing courses. Descriptions of these courses are available in the Searchable Class Schedule on Murphy Online, View Searchable Class Schedule

Schedule Details

Location Time Day(s)
MATH 114 - 06 Calculus II - T - R - - - 1330 - 1510 OSS 227

Days of Week:

- T - R - - -

Time of Day:

1330 - 1510

Location:

OSS 227

Course Registration Number:

41971 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Arkady Shemyakin

Techniques of integration; applications of integration; infinite series; parametric/polar equations. Offered Fall, Spring and Summer. Prerequisite: a grade of C- or above in MATH 112 or in MATH 113 or MATH 109

Schedule Details

Location Time Day(s)
MATH 313 - 02 Probability - T - R - - - 1525 - 1700 OSS 214

Days of Week:

- T - R - - -

Time of Day:

1525 - 1700

Location:

OSS 214

Course Registration Number:

41994 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Arkady Shemyakin

Probability theory in discrete and continuous sample spaces; random variables and distribution functions; moments; the moment-generating function; functions of random variables; law of large numbers; central limit theorem. Offered Fall and Spring. Prerequisites: A grade of C- or above in MATH 200 (may be taken concurrently with consent of instructor) NOTE: Students who receive credit for MATH 313 may not receive credit for MATH 303.

Schedule Details

Location Time Day(s)

J-Term 2019 Courses

J-Term 2019 Courses
Course - Section Title Days Time Location

Spring 2019 Courses

Spring 2019 Courses
Course - Section Title Days Time Location
STAT 333 - D01 Applied Statistical Methods M - W - - - - 1525 - 1700 OSS 214

Days of Week:

M - W - - - -

Time of Day:

1525 - 1700

Location:

OSS 214

Course Registration Number:

20637 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Arkady Shemyakin

Regression and exponential smoothing methods; Stochastic Time Series: auto- and cross-correlation, autoregressive moving average models; application to forecasting. Prerequisites: MATH 303 or 314 or STAT 314 or permission of instructor

Schedule Details

Location Time Day(s)
STAT 333 - D02 Applied Statistical Methods - T - R - - - 1330 - 1510 OSS 214

Days of Week:

- T - R - - -

Time of Day:

1330 - 1510

Location:

OSS 214

Course Registration Number:

20999 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Arkady Shemyakin

Regression and exponential smoothing methods; Stochastic Time Series: auto- and cross-correlation, autoregressive moving average models; application to forecasting. Prerequisites: MATH 303 or 314 or STAT 314 or permission of instructor

Schedule Details

Location Time Day(s)
STAT 370 - 01 Bayesian Models - T - R - - - 1525 - 1700 OSS 214

Days of Week:

- T - R - - -

Time of Day:

1525 - 1700

Location:

OSS 214

Course Registration Number:

22368 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Arkady Shemyakin

The course covers a range of statistical models used in applications including: Actuarial Science, Finance, Health and Social Sciences. It is oriented towards practical model construction and problem solving. Review of parametric statistical models and principles of statistical inference. Application to loss and ruin models. Construction of empirical and parametric models and model selection. Credibility theory. Simulation. Offered every other year. Prerequisite: MATH 313 and STAT 314 or STAT 220 and STAT 320

Schedule Details

Location Time Day(s)