Shayle Robert Searle PhD (26 April 1928 – 18 February 2013) was a New Zealand mathematician who was professor emeritus of biological statistics at Cornell University.[1] He was a leader in the field of linear and mixed models in statistics, and published widely on the topics of linear models, mixed models, and variance component estimation.[2]

Searle was one of the first statisticians to use matrix algebra in statistical methodology, and was an early proponent of the use of applied statistical techniques in animal breeding.

He died at his home in Ithaca, New York.

Education

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Employment

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  • Research statistician – New Zealand Dairy Board – 1953 to 1955, 1959 to 1962
  • Statistician – University Computing Center, Cornell University – 1962 to 1965
  • Professor of biological statistics – Cornell University – 1965 to 1996

Honours

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Bibliography

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Books

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  • Shayle R. Searle (2009). The Collected Works of Shayle R. Searle. New York: Wiley. ISBN 978-0-470-55606-1.
  • Neuhaus, John William; McCulloch, Charles E.; Shayle R. Searle (2008). Generalized, Linear, and Mixed Models (Wiley Series in Probability and Statistics) (2nd ed.). New York: Wiley-Interscience. ISBN 978-0-470-07371-1.
  • Shayle R. Searle (2006). Linear Models for Unbalanced Data (Wiley Series in Probability and Statistics). New York: Wiley-Interscience. ISBN 0-470-04004-1.
  • McCulloch, Charles E.; Shayle R. Searle; Casella, George (2006). Variance Components (Wiley Series in Probability and Statistics). New York: Wiley-Interscience. ISBN 0-470-00959-4.
  • Shayle R. Searle (2006). Matrix Algebra Useful for Statistics (Wiley Series in Probability and Statistics). New York: Wiley-Interscience. ISBN 0-470-00961-6.
  • McCulloch, Charles E.; Searle, Shayle R. (2001). Generalized, Linear, and Mixed Models (1st ed.). Chichester: John Wiley & Sons. ISBN 0-471-19364-X.
  • Willett, Lois Schertz; Searle, S. R. (2001). Matrix algebra for applied economics. Chichester: John Wiley & Sons. ISBN 0-471-32207-5.
  • Searle, S. R. (1971). Linear models. New York: Wiley. ISBN 0-471-18499-3.
  • Hausman, Warren H.; Searle, S. R. (1970). Matrix algebra for business and economics. New York: Wiley-Interscience. ISBN 0-471-76941-X.
  • Shayle R. Searle (1966). Matrix Algebra for the Biological Sciences (Series on Quantitative Methods for Biologists & Medical Scientists). John Wiley & Sons Inc. ISBN 0-471-76930-4.

Selected journal articles

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2000s
1990s
1980s
1970s
  • Searle, S.R. (1979). "On inverting circulant matrices". Linear Algebra and Its Applications. 25: 77–89. doi:10.1016/0024-3795(79)90007-7. hdl:1813/32683.
  • Henderson, H. V.; Searle, S. R. (1979). "Vec and Vech Operators for Matrices, with Some Uses in Jacobians and Multivariate Statistics". The Canadian Journal of Statistics. 7 (1): 65–81. doi:10.2307/3315017. JSTOR 3315017.
  • Searle, S. R. (1979). "Alternative covariance models for the 2-way crossed classification". Communications in Statistics - Theory and Methods. 8 (8): 799–818. doi:10.1080/03610927908827800.
  • Searle, S. R. (1979). "Annotated Computer Output for Analysis of Variance of Unequal-Subclass- Numbers Data". The American Statistician. 33 (4): 222–223. doi:10.2307/2683742. JSTOR 2683742.
  • Searle, SR (1979). "Discussion of H. Ahrens' An invariance property for first and second order moments of estimated variance-covariance components (19th Session on Stochastics)". Biometrical Journal. 21: 389–398. doi:10.1002/bimj.4710210407. hdl:1813/32735.
  • Searle, S. R.; Henderson, H. V. (1979). "Dispersion Matrices for Variance Components Models". Journal of the American Statistical Association. 74 (366): 465–470. doi:10.2307/2286357. JSTOR 2286357.
  • Searle, S.R. (1978). "A univariate formulation of the multivariate linear model". In David, H.A. (ed.). Contributions to Survey Sampling and Applied Statistics, Papers in Honor of H.O. Hartley. New York: Academic Press. pp. 181–189. ISBN 978-0122047503.
  • Swallow, W. H.; Searle, S. R. (1978). "Minimum Variance Quadratic Unbiased Estimation (MIVQUE) of Variance Components". Technometrics. 20 (3): 265–272. doi:10.2307/1268135. JSTOR 1268135.
  • Searle, S. R. (1977). "Proof". International Journal of Mathematical Education in Science and Technology. 8 (2): 185–192. doi:10.1080/0020739770080207.
  • Corbeil, R. R.; Searle, S. R. (1976). "A Comparison of Variance Component Estimators". Biometrics. 32 (4): 779–791. doi:10.2307/2529264. hdl:1813/32662. JSTOR 2529264.
  • Corbeil, R. R.; Searle, S. R. (1976). "Restricted Maximum Likelihood (REML) Estimation of Variance Components in the Mixed Model". Technometrics. 18 (1): 31–38. doi:10.2307/1267913. JSTOR 1267913.
  • Henderson, C. R.; Searle, S. R.; Schaeffer, L. R. (1974). "The Invariance and Calculation of Method 2 for Estimating Variance Components". Biometrics. 30 (4): 583–588. doi:10.2307/2529223. JSTOR 2529223.
  • Searle, S. R.; Rounsaville, T. R. (1974). "A Note on Estimating Covariance Components". The American Statistician. 28 (2): 67–68. doi:10.2307/2683606. JSTOR 2683606.
  • Searle, S. R. (1973). "On Publishing Extended Abstracts, and Reviews". The American Statistician. 27 (4): 155–157. doi:10.2307/2684045. JSTOR 2684045.
  • Rudan, J. W.; Searle, S. R. (1971). "323. Note: Large Sample Variances of Maximum Likelihood Estimators of Variance Components in the 3-Way Nested Classification, Random Model, with Unbalanced Data". Biometrics. 27 (4): 1087–1091. doi:10.2307/2528844. JSTOR 2528844.
  • Searle, S. R. (1971). "A Biometrics Invited Paper. Topics in Variance Component Estimation". Biometrics. 27 (1): 1–76. doi:10.2307/2528928. JSTOR 2528928.
  • Townsend, E. C.; Searle, S. R. (1971). "Best Quadratic Unbiased Estimation of Variance Components from Unbalanced Data in the 1-Way Classification". Biometrics. 27 (3): 643–657. doi:10.2307/2528602. hdl:1813/32414. JSTOR 2528602.
  • Searle, S. R. (1970). "Large Sample Variances of Maximum Likelihood Estimators of Variance Components Using Unbalanced Data". Biometrics. 26 (3): 505–524. doi:10.2307/2529105. JSTOR 2529105.
  • Searle, S. R.; Fawcett, R. F. (1970). "Expected Mean Squares in Variance Components Models Having Finite Populations". Biometrics. 26 (2): 243–254. doi:10.2307/2529072. JSTOR 2529072.
1960s
1950s

References

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Further reading

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