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Featured researches published by Toke Jayachandran.


IEEE Transactions on Reliability | 1976

A Comparison of Reliability Growth Models

Toke Jayachandran; Louis R. Moore

A reliability growth model is an analytic tool that accounts for changes in reliability due to design modifications and other corrective actions taken during the develpment, production, and use of a new piece of equipment. This paper describes a simulation study, and its conclusions, comparing four general reliability growth models that have been proposed in the reliability literature. Details of the simulation results are available in a separate Supplement.


Journal of Statistical Computation and Simulation | 1984

Tables for a new multivariate goodness-of-fit test

Toke Jayachandran; Richard Franke

We present tables of critical values for a new multivariate goodness-of-fit test introduced by Foutz. Some details of our improved asymptotic approximation and evaluation of its accuracy are given. An example showing the application of the method is given.


The American Statistician | 1970

On the Distribution of a Difference of Two Scaled Chi-Square Random Variables

Toke Jayachandran; Donald R. Barr

by tending to make the animals remain in the protected area, the number of surviving animals is increased from 263 to 784. It can be noted that since the death rate, is between P21 and P31, i.e. 0.1 < death rate, <0.5 and the birth rate is bounded by M22 and M33, i.e. birth rate equals 0.1, extinction is inevitable. Any efforts to reduce the death rate or to increase the birth rate would change the transition matrix. Further reduction in death rates may be feasible by increased enforcement or patrols, increased hunting license fees, etc. By way of further example, another transition matrix P could be defined as P = .5 .2 .3


Journal of The Australian Mathematical Society | 1971

Amenable transformation semigroups

Carroll Wilde; Toke Jayachandran

For any set X denote by m ( X ) the Banach space of all bounded real-valued functions on X , equipped with the supremum norm, and denote by ( X ) the semigroup (under functional composition) of all transformations of X , i.e. mappings with domain X and range contained in X . A pair ( X, S ), where S is a subsernigroup of ( X ), will be called a transformation semigroup. Important examples are obtained by letting X be the underlying set in an abstract semigroup and considering the pairs ( X, S 1 ) and ( X , S 2 ), where S 1 [Sn] denotes the set of left [right] multiplication mappings of X . We shall call transformation semigroups in these classes of examples l-[r-] semigroups.


Archive | 1982

Properties of a Multivariate Goodness-of-Fit Test.

Toke Jayachandran; Richard Franke


Archive | 1980

A study of the properties of a new goodness-of-fit test

Toke Jayachandran; Richard Franke


Archive | 1993

The Determination of Radiosonde Geopotential Height Biases by the Navy's Gobal Data Assimilation System

Nancy L. Baker; Richard Franke; Toke Jayachandran


Archive | 1991

Quality control of meteorological observations

Toke Jayachandran; Richard Franke


Naval Research Logistics Quarterly | 1983

A note on a prediction interval for a first‐order Gauss Markov process

Toke Jayachandran


Naval Research Logistics Quarterly | 1983

On prediction intervals for normal samples

Toke Jayachandran

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Richard Franke

Naval Postgraduate School

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Donald R. Barr

Naval Postgraduate School

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Louis R. Moore

University of North Carolina at Chapel Hill

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Carroll Wilde

Naval Postgraduate School

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D. R. Barr

Naval Postgraduate School

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W. E. Coleman

Naval Postgraduate School

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