6533b826fe1ef96bd1283b17
RESEARCH PRODUCT
Parameter orthogonality and conditional profile likelihood: the exponential power function case
Gianna Ageòsubject
Statistics and ProbabilityStatisticsApplied mathematicsProbability density functionDensity estimationConditional probability distributionLikelihood functionLikelihood principleConditional varianceShape parameterExponential functionMathematicsdescription
Orthogonality, according to Fisher’s metrics, between the parameters of a probability density function, as well as giving rise to a series of statistical implications, makes it possible to express a function of conditional profile likelihood with better properties than the ordinary profile likelihood function. In the present paper the parameters of exponential power function are made orthogonal and the conditional profile likelihood of the shape parameter p is determined in order to study its properties with reference to p estimation. Moreover, by means of a simulation plan, a comparison is made between the estimates of p obtained from the conditional profile log-likelihood and those obtained from the ordinary profile log-likelihood.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 1999-01-01 | Communications in Statistics - Theory and Methods |