Abstract
The earliest method of estimation of statistical parameters is the method of least squares due to Mark off. A set of observations whose expectations are linear functions of a number of unknown parameters being given, the problem which Markoff posed for solution is to find out a linear function of observations whose expectation is an assigned linear function of the unknown parameters and whose variance is a minimum. There is no assumption about the distribution of the observations except that each has a finite variance.
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References
Aitken, A.C., (1941), On the Estimation of Statistical Parameters. Proc. Roy. Soc. Edin., 61, 56–62.
Bhattacharya, A., (1942), On Discrimination and Divergence. Proc. Sc. Cong.
Fisher, R.A., (1921), On the Mathematical Foundations of Theoretical Statistics. Phil. Trans. Roy. Soc. A, 222, 309–368.
Koopman, B.O., (1936), On Distributions Admitting Sufficient Statistics. Trans. Am. Math. Soc., 39, 399–409.
Mahalanobis, P.C., (1936), On the Generalised Distance in Statistics. Proc. Nat. Inst. Sc. Ind., 2, 49–55.
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© 1992 Springer Science+Business Media New York
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Rao, C.R. (1992). Information and the Accuracy Attainable in the Estimation of Statistical Parameters. In: Kotz, S., Johnson, N.L. (eds) Breakthroughs in Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0919-5_16
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DOI: https://doi.org/10.1007/978-1-4612-0919-5_16
Publisher Name: Springer, New York, NY
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