Maximum Likelihood Estimation of the Survival Functions ofNStochastically Ordered Random Variables

1985 ◽  
Vol 80 (392) ◽  
pp. 1012-1019 ◽  
Author(s):  
Carol J. Feltz ◽  
Richard L. Dykstra
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Random Variables ◽  
Likelihood Estimation ◽  
Survival Functions

scholarly journals DECONVOLUTING PREFERENCES AND ERRORS: A MODEL FOR BINOMIAL PANEL DATA

2010 ◽  
Vol 26 (6) ◽  
pp. 1846-1854 ◽  
Author(s):  
Mogens Fosgerau ◽  
Søren Feodor Nielsen
Keyword(s):  
Maximum Likelihood ◽  
Panel Data ◽  
Maximum Likelihood Estimation ◽  
Unknown Parameter ◽  
Random Variables ◽  
Likelihood Estimation ◽  
Estimation Procedure ◽  
Choice Experiments ◽  
Stated Choice ◽  
Stated Choice Experiments

In many stated choice experiments researchers observe the random variablesVt,Xt, andYt= 1{U+δ⊤Xt+ εt<Vt},t≤T, whereδis an unknown parameter andUand εtare unobservable random variables. We show that under weak assumptions the distributions ofUand εtand also the unknown parameterδcan be consistently estimated using a sieved maximum likelihood estimation procedure.

scholarly journals On some properties of Generalized Transmuted Kumaraswamy distribution

2019 ◽  
pp. 577-586
Author(s):  
Aliyu Ismail Ishaq ◽  
Abubakar Usman ◽  
Tasiu Musa ◽  
Samson Agboola
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Statistical Properties ◽  
Survival Functions ◽  
Kumaraswamy Distribution ◽  
Proposed Model ◽  
Method Of Maximum Likelihood ◽  
The Family ◽  
Lifetime Model

ABSTRACTThis articles introduces a new lifetime model called the generalized transmuted Kumaraswamy distribution which extends the Kumaraswamy distribution from the family proposed by Nofal et al., (2017). We provide hazard and survival functions of the proposed distribution. The statistical properties of the proposed model are provided and the method of Maximum Likelihood Estimation (MLE) was proposed in estimating its parameters.

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