A modified bessel function model in life testing

Metrika ◽  
1967 ◽  
Vol 11 (1) ◽  
pp. 133-144 ◽  
Author(s):  
Samir Kumar Bhattacharya
2013 ◽  
Vol 16 ◽  
pp. 78-108 ◽  
Author(s):  
Andrew R. Booker ◽  
Andreas Strömbergsson ◽  
Holger Then

AbstractUsing the paths of steepest descent, we prove precise bounds with numerical implied constants for the modified Bessel function${K}_{ir} (x)$of imaginary order and its first two derivatives with respect to the order. We also prove precise asymptotic bounds on more general (mixed) derivatives without working out numerical implied constants. Moreover, we present an absolutely and rapidly convergent series for the computation of${K}_{ir} (x)$and its derivatives, as well as a formula based on Fourier interpolation for computing with many values of$r$. Finally, we have implemented a subset of these features in a software library for fast and rigorous computation of${K}_{ir} (x)$.


1953 ◽  
Vol 1 (3) ◽  
pp. 119-120 ◽  
Author(s):  
Fouad M. Ragab

§ 1. Introductory. The formula to be established iswhere m is a positive integer,and the constants are such that the integral converges.


1961 ◽  
Vol 14 (4) ◽  
pp. 598 ◽  
Author(s):  
EJ Williams

Though randomly moving insects released from a central point in a uniform environment are often found to be distributed according to a circular normal distribution, their larvae will not conform to this distribution. When such insects lay at a constant rate and are subject to constant mortality, their larvae are found to be spatially distributed according to a highly peaked frequency function, depending on the modified Bessel function of the second kind. This theoretical conclusion is in good agreement with published data. Some of the properties of the theoretical distribution are discussed.


1968 ◽  
Vol 10 (12) ◽  
pp. 1101-1104 ◽  
Author(s):  
R D Gibson ◽  
K J Whiteman

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