Related Research Articles
A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. Informally, this may be thought of as, "What happens next depends only on the state of affairs now." A countably infinite sequence, in which the chain moves state at discrete time steps, gives a discrete-time Markov chain (DTMC). A continuous-time process is called a continuous-time Markov chain (CTMC). Markov processes are named in honor of the Russian mathematician Andrey Markov.
A hidden Markov model (HMM) is a Markov model in which the observations are dependent on a latent Markov process. An HMM requires that there be an observable process whose outcomes depend on the outcomes of in a known way. Since cannot be observed directly, the goal is to learn about state of by observing By definition of being a Markov model, an HMM has an additional requirement that the outcome of at time must be "influenced" exclusively by the outcome of at and that the outcomes of and at must be conditionally independent of at given at time Estimation of the parameters in an HMM can be performed using maximum likelihood. For linear chain HMMs, the Baum–Welch algorithm can be used to estimate the parameters.
In statistics, Markov chain Monte Carlo (MCMC) is a class of algorithms used to draw samples from a probability distribution. Given a probability distribution, one can construct a Markov chain whose elements' distribution approximates it – that is, the Markov chain's equilibrium distribution matches the target distribution. The more steps that are included, the more closely the distribution of the sample matches the actual desired distribution.
In the mathematical theory of stochastic processes, variable-order Markov (VOM) models are an important class of models that extend the well known Markov chain models. In contrast to the Markov chain models, where each random variable in a sequence with a Markov property depends on a fixed number of random variables, in VOM models this number of conditioning random variables may vary based on the specific observed realization.
David Amiel Freedman was a Professor of Statistics at the University of California, Berkeley. He was a distinguished mathematical statistician whose wide-ranging research included the analysis of martingale inequalities, Markov processes, de Finetti's theorem, consistency of Bayes estimators, sampling, the bootstrap, and procedures for testing and evaluating models. He published extensively on methods for causal inference and the behavior of standard statistical models under non-standard conditions – for example, how regression models behave when fitted to data from randomized experiments. Freedman also wrote widely on the application—and misapplication—of statistics in the social sciences, including epidemiology, public policy, and law.
Jeffrey Seth Rosenthal is a Canadian statistician and nonfiction author. He is a professor in the University of Toronto's department of statistics, cross-appointed with its department of mathematics.
James Laurie Snell was an American mathematician and educator.
Cyrus Derman was an American mathematician and amateur musician who did research in Markov decision process, stochastic processes, operations research, statistics and a variety of other fields.
Dalla Lana School of Public Health is the school of public health at the University of Toronto. It was founded in 1927, and was home for 50 years to Connaught Laboratories, a manufacturer of vaccines, insulin, and many other pharmaceutical products. Having grown to be the largest cluster of public health scholars in Canada, the school was revitalized in 2008 with the support of a major gift from the Dalla Lana family.
Priscilla E. (Cindy) Greenwood is a Canadian mathematician who is a professor emeritus of mathematics at the University of British Columbia. She is known for her research in probability theory.
Geoffrey John McLachlan FAA is an Australian researcher in computational statistics, machine learning and pattern recognition. McLachlan is best known for his work in classification and finite mixture models. He is the joint author of five influential books on the topics of mixtures and classification, as well as their applications. Currently, McLachlan is a Professor of statistics within the School of Mathematics and Physics at the University of Queensland.
Gillian Einstein is a faculty member at the Dalla Lana School of Public Health and the Department of Psychology at the University of Toronto, and holder of the inaugural Wilfred and Joyce Posluns Chair in Women's Brain Health and Aging.
Michael Barrett Woodroofe was an American probabilist and statistician. He was a professor of statistics and of mathematics at the University of Michigan, where he was the Leonard J. Savage Professor until his retirement. He was noted for his work in sequential analysis and nonlinear renewal theory, in central limit theory, and in nonparametric inference with shape constraints.
Sharon-Lise Teresa Normand is a Canadian biostatistician whose research centers on the evaluation of the quality of care provided by physicians and hospitals, and on the health outcomes for medical devices and medical procedures. She is a professor in the Department of Health Care Policy at the Harvard Medical School and in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health.
Mary Elinore Thompson is a Canadian statistician. She is Distinguished Professor Emerita of Statistics and Actuarial Science at the University of Waterloo, the former president of the Statistical Society of Canada, and the founding scientific director of the Canadian Statistical Sciences Institute. Her research interests include survey methodology and statistical sampling; she is also known for her work applying statistics to guide tobacco control policy.
Lynn Margaret Batten was a Canadian-Australian mathematician known for her books about finite geometry and cryptography, and for her research on the classification of malware.
Janet Turk Wittes is an American statistician known for her work on clinical trials.
Lei Sun is a Chinese and Canadian statistical geneticist at the University of Toronto, where she is affiliated both with the department of biostatistics in the Dalla Lana School of Public Health and the department of statistical sciences in the faculty of arts and science.
Laura C. A. Rosella is a Canadian epidemiologist who is an Associate Professor at the Dalla Lana School of Public Health in the University of Toronto. She studies public health and the social determinants of health. Rosella holds a Canada Research Chair in Population Health Analytics.
References
- 1 2 "Wendy Lou", Faculty database, Dalla Lana School of Public Health , retrieved 2018-12-16
- 1 2 3 4 "Dr. W.Y. Wendy Lou, Professor" (PDF), Speaker biography for SCV 2008 conference, Academia Sinica Institute of Statistical Science, retrieved 2018-12-16
- ↑ Reviews of Distribution Theory of Runs and Patterns and Its Applications:
- Hildebrand, Martin V. (2005), Mathematical Reviews, doi:10.1142/4669, ISBN 978-981-02-4587-0, MR 2000533
{{citation}}: CS1 maint: untitled periodical (link) - Goldie, Charles M. (March 2005), Journal of the American Statistical Association, 100 (469): 349–350, doi:10.1198/jasa.2005.s3, JSTOR 27590545, S2CID 118779299
{{citation}}: CS1 maint: untitled periodical (link)
- Hildebrand, Martin V. (2005), Mathematical Reviews, doi:10.1142/4669, ISBN 978-981-02-4587-0, MR 2000533
- ↑ Prof. Wendy Lou honored as Fellow of the American Statistical Association, Dalla Lana School of Public Health, 10 June 2013, retrieved 2018-12-16
- ↑ Thompson, Mary E. (2014), "Reflections on women in statistics in Canada", in Lin, Xihong; Genest, Christian; Banks, David L.; Molenberghs, Geert; Scott, David W.; Wang, Jane-Ling (eds.), Past, Present, and Future of Statistical Science, CRC Press, pp. 203–216, ISBN 9781482204988 . See in particular p. 210.
| International | |
|---|---|
| National | |
