Generalized variable method inference for the location parameter of the general half-normal distribution
S Gunasekera, MMA Ananda - Journal of Statistical Computation …, 2015 - Taylor & Francis
Journal of Statistical Computation and Simulation, 2015•Taylor & Francis
This paper considers the development of inferential techniques based on the generalized
variable method (GV-Method) for the location parameter of the general half-normal
distribution. We are interested in hypothesis testing of, and interval estimation for, the
location parameter. Body fat data, urinary excretion rate data, and simulated data are used
to illustrate the application and to demonstrate the advantages of the proposed GV-Method
over the large-sample method and the Bayesian method.
variable method (GV-Method) for the location parameter of the general half-normal
distribution. We are interested in hypothesis testing of, and interval estimation for, the
location parameter. Body fat data, urinary excretion rate data, and simulated data are used
to illustrate the application and to demonstrate the advantages of the proposed GV-Method
over the large-sample method and the Bayesian method.
This paper considers the development of inferential techniques based on the generalized variable method (GV-Method) for the location parameter of the general half-normal distribution. We are interested in hypothesis testing of, and interval estimation for, the location parameter. Body fat data, urinary excretion rate data, and simulated data are used to illustrate the application and to demonstrate the advantages of the proposed GV-Method over the large-sample method and the Bayesian method.
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