Bounded risk estimation of linear combinations of the location and scale parameters in exponential distributions under two-stage sampling

2007 ◽  
Vol 137 (11) ◽  
pp. 3672-3686 ◽  
Author(s):  
N. Mukhopadhyay ◽  
S. Zacks
Keyword(s):  
Risk Estimation ◽  
Exponential Distributions ◽  
Two Stage ◽  
Linear Combinations ◽  
Scale Parameters ◽  
Bounded Risk ◽  
Bounded Risk Estimation

scholarly journals Bounded risk estimation of a finite population mean optimal strategies

1988 ◽  
Vol 7 (2) ◽  
pp. 91-109 ◽  
Author(s):  
Nitis Mukhopadhyay ◽  
Pranab Kumar Sen ◽  
Bikas Kumar Sinha
Keyword(s):  
Finite Population ◽  
Risk Estimation ◽  
Optimal Strategies ◽  
Population Mean ◽  
Bounded Risk ◽  
Bounded Risk Estimation

A geometric interpretation of the relations between the exponential and generalized Erlang distributions

1982 ◽  
Vol 14 (04) ◽  
pp. 885-897 ◽  
Author(s):  
Michel Dehon ◽  
Guy Latouche
Keyword(s):  
Vector Space ◽  
Convex Subset ◽  
Geometric Interpretation ◽  
Distribution Functions ◽  
Real Vector ◽  
Exponential Distributions ◽  
Geometric Aspect ◽  
Linear Combinations ◽  
Exponential Random Variables ◽  
Erlang Distributions

Linear combinations of exponential distribution functions are considered, and the class of distribution functions so obtainable is investigated. Convex combinations correspond to hyperexponential distributions, while non-convex combinations yield, among other, generalized Erlang distributions obtainable as sums of independent exponential random variables with different parameters. For a given number n of different exponential distributions, the class investigated is an (n – 1)-dimensional convex subset of the n-dimensional real vector space generated by the n distribution functions. The geometric aspect of this subset is revealed, together with the location of hyperexponential and generalized Erlang distributions.

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