Source: Statist. Sci.
Volume 24, Number 2
Born in New Zealand, Shayle Robert Searle earned a bachelor’s degree (1949) and a master’s degree (1950) from Victoria University, Wellington, New Zealand. After working for an actuary, Searle went to Cambridge University where he earned a Diploma in mathematical statistics in 1953. Searle won a Fulbright travel award to Cornell University, where he earned a doctorate in animal breeding, with a strong minor in statistics in 1959, studying under Professor Charles Henderson. In 1962, Cornell invited Searle to work in the university’s computing center, and he soon joined the faculty as an assistant professor of biological statistics. He was promoted to associate professor in 1965, and became a professor of biological statistics in 1970. Searle has also been a visiting professor at Texas A&M University, Florida State University, Universität Augsburg and the University of Auckland. He has published several statistics textbooks and has authored more than 165 papers. Searle is a Fellow of the American Statistical Association, the Royal Statistical Society, and he is an elected member of the International Statistical Institute. He also has received the prestigious Alexander von Humboldt U.S. Senior Scientist Award, is an Honorary Fellow of the Royal Society of New Zealand and was recently awarded the D.Sc. Honoris Causa by his alma mater, Victoria University of Wellington, New Zealand.
Aitken, A. C. (1939). Determinants and Matrices. Oliver and Boyd, Edinburgh.
Bose, R. C. (1949). Least Squares Aspects of Analysis of Variance. Institute of Statistics Mimeo Series 9. Univ. North Carolina, Chapel Hill.
Callow, E. H. and Searle, S. R. (1956). Comparative studies of meat: V Factors affecting the iodine number of the fat from the fatty and muscular tissues of cattle. J. Agricultural Science 48 63–73.
Graybill, F. A. (1961). An Introduction to Linear Statistical Models. McGraw-Hill, New York.
Mathematical Reviews (MathSciNet): MR126316
Hartley, H. O. and Rao, J. N. K. (1967). Maximum likelihood estimation for the mixed analysis of variance model. Biometrika 54 93–108.
Mathematical Reviews (MathSciNet): MR216684
Henderson, C. R. (1953). Estimation of variance and covariance components. Biometrics 9 226–252.
Mathematical Reviews (MathSciNet): MR55650
Henderson, C. R., Kempthorne, O., Searle, S. R. and Von Krozigk (1959). Estimation of environmental and genetic trends from records subject to culling. Biometrics 15 192–218.
McCulloch, C. E. and Searle, S. R. (2001). Generalized, Linear, and Mixed Models. Wiley, New York.
Penrose, R. A. (1955). A generalized inverse for matrices. Proc. Cambridge Philosophical Society 51 406–413.
Mathematical Reviews (MathSciNet): MR69793
Rao, C. R. (1962). A note on a generalized inverse of a matrix with applications to problems in mathematical statistics. J. Roy. Statist. Soc. Ser. B. 24 152–158.
Mathematical Reviews (MathSciNet): MR138149
Searle, S. R. (1951). Probability: Difficulties of definition. J. Inst. Actuaries Students’ Soc. 10 204–212.
Mathematical Reviews (MathSciNet): MR47269
Searle, S. R. (1956). Matrix methods in variance and covariance component analysis. Ann. Math. Statist. 27 737–748.
Mathematical Reviews (MathSciNet): MR81051
Searle, S. R. (1958). Sampling variances of estimates of components of variance. Ann. Math. Statist. 29 167–178.
Mathematical Reviews (MathSciNet): MR93879
Searle, S. R. and Henderson, C. R. (1961). Variance components in the unbalanced 2-way nested classification. Ann. Math. Statist. 32 1161–1166.
Mathematical Reviews (MathSciNet): MR133930
Searle, S. R. (1966). Matrix Algebra for the Biological Sciences. Wiley Chichester.
Searle, S. R. (1982). Matrix Algebra Useful for Statistics. Wiley, New York.
Mathematical Reviews (MathSciNet): MR670947
Searle, S. R. (1971). Linear Models. Wiley, Chichester. (1997, Wiley Classics Library.)
Searle, S. R. (1993). Analysis of variance computing then and now, with reference to unbalanced data. In Proceedings 18th SAS Users’ Group Conference 1077–1087.
Searle, S. R. (1997). Linear Models for Unbalanced Data. Wiley, New York.
Mathematical Reviews (MathSciNet): MR907471
Searle, S. R., Casella, G. and McCulloch, C. E. (1992). Variance Components. Wiley, New York.
Searle, S. R. and Hausman, W. H. (1970). Matrix Algebra for Business and Economics. Wiley, New York.
Wicksell, S. D. (1930). Remarks on regression. Ann. Math. Statist. 1 1.
Williams, E. J. (1959). Regression Analysis. Wiley, New York.
Mathematical Reviews (MathSciNet): MR112212