Murray Rosenblatt ( born September 7, 1926 in New York City ) is an American mathematical statistician, a professor at the University of California, San Diego.
Rosenblatt studied at the City College of New York with a bachelor 's degree in 1946 and from Cornell University with a master's degree in 1946 and his doctorate at Mark Kac in 1949 ("On distributions of Certain Wiener functionals "). From 1950 he was Instructor and then Assistant Professor of Statistics at the University of Chicago, 1956 Associate Professor at Indiana University and from 1959 Professor of Applied Mathematics at Brown University. From 1964 he was at the University of California, San Diego.
1966 He was a visiting professor at University College London and in 1976 at the Australian National University and 1979 Fellow at Churchill College, Cambridge.
Rosenblatt deals with stochastic processes, time series analysis and mathematical statistics ( nonparametric methods). He wrote important contributions to estimation of density functions, central limit theorems under strong mixing conditions, Markov processes and processes with long-term memory, time series analysis.
The Rosenblatt transformation is named after him and the Rosenblatt process.
He is a member of the National Academy of Sciences (1984 ), Fellow of the American Association for the Advancement of Science and the Institute of Mathematical Statistics. 1965/66 and 1971/72 he was a Guggenheim Fellow. In 2013 he became a Fellow of the American Mathematical Society and he is a Fellow of the Society for Industrial and Applied Mathematics ( SIAM ).
He has been married since 1949 and has a son and a daughter.
- Richard A. Davis, Keh -Shin Lii, Dimitris N. Politis (Editor) Selected Works of Murray Rosenblatt, Springer Verlag 2011
- With Ulf Grenander Statistical Analysis of Stationary Time Series, American Mathematical Society, 1984 ( first Stockholm 1956)
- Markov processes; structure and asymptotic behavior, Springer Verlag 1971
- Stationary sequences and random fields, Birkhäuser 1985
- Random Processes, Oxford University Press, 1962, 2nd edition Springer Verlag 1974
- Gaussian and non- Gaussian linear time series and random fields, Springer Verlag 2000
- Independence and dependence, Proc. 4th Berkeley Symposium on Mathematical Statistics Prob. , II, University of California Press, 1961, pp. 431-443
- A central limit theorem and a strong mixing condition, Proc. Nat. Acad. Sci. USA, 42, 1956, 43-47