Prasanta Chandra Mahalanobis

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Mahalanobis, Prasanta Chandra

 

Born June 29, 1893, in Calcutta; died there June 27, 1972. Indian statistician and economist.

Mahalanobis was educated at the University of Calcutta (1912) and at Cambridge (1915). From 1931 he headed the India Statistical Institute (Calcutta), which he had established. He was founder (1933) and editor of the statistical journal Sankhya. He served as a member of the Planning Commission of India (1955-67) and as a government advisor on problems of statistics (1949-67).

Mahalanobis’ theoretical works and practical recommendations proceed from positions of petit bourgeois radicalism. He called for the industrialization of India on a basis of accelerated development of the state sector and the centralization of material and monetary resources in the hands of the state, and he favored the simultaneous further development of small enterprise. Mahalanobis played an important part in the formation and development of economic and scientific ties between India and the USSR. He was a foreign member of the Academy of Sciences of the USSR (1958) and a member of the Royal Society of London (1945).

WORKS

Some Observations on the Process of the Growth of National Income. [Calcutta, 1953.]
Talks on Planning. Bombay-Calcutta [1961].
The Approach of Operational Research to Planning in India. Bombay-Calcutta [1963].
In Russian translation:
Vyborochnye obsledovaniia v Indii (Novyi opyt Indiiskogo statisticheskogo instituta). Moscow, 1958. (Translated from English.)
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Outlier samples were removed from the calibration set using Diagnostics based on Mahalanobis distance within the TQ Analyst software.
Assessment of alternative approaches for bioclimatic modelling with special emphasis on the Mahalanobis distance.
The Mahalanobis distance is a measure of the distance between a point P and a distribution D.
Values greater than or equal to three standard deviations (SD) from a variable mean were considered univariate outliers and cases with a Mahalanobis distance greater than a critical [chi square] (13) at p [less than or equal to] .
Closest" was defined using the Mahalanobis distance between the means--the most standard of multivariate distance measures--and it is essentially the sum of the squares of the differences in means in units of the standard deviation with an adjustment that reduces the redundancy of variables that are highly correlated (see Rubin 1979, 1980).
The approach is known as the Nearest Available Mahalanobis Metric Matching within Calipers Defined by the Propensity Score.
6) An alternative normalization method, based on the Mahalanobis transformation, accounts for the correlations across components of [x.
We considered the different metrics because, while Euclidean gives equal weight to all data, diagonal accounts for different variances, with Mahalanobis additionally accounting for correlation between data.
Standardized values, Studentized values and Mahalanobis distance were used to determine outliers at first.
The data were next examined for multivariate outliers, using as the criterion Mahalanobis distance at p < .