Y. Komori and H. Hirose (2004), Easy estimation by a new parameterization
for the three-parameter lognormal distribution, Journal of Statistical
Computation and Simulation, 74 (1), 63-74.
Abstract
A new parameterization and algorithm are proposed for seeking the primary
relative maximum of the likelihood function in the three-parameter lognormal
distribution. The parameterization yields the dimension reduction of the
three-parameter estimation problem to a two-parameter estimation problem
on the basis of an extended lognormal distribution. The algorithm provides
the way of seeking the profile of an object function in the two-parameter
estimation problem. It is simple and numerically stable because it is constructed
on the basis of the bisection method. The profile clearly and easily shows
whether a primary relative maximum exists or not, and also gives a primary
relative maximum certainly if it exists.
Note
The journal is abstracted/indexed in MathSciNet and Web of Science. Thus, additional information about the paper is obtainable from the databases.
The following are source files implimenting the algorithm proposed in the paper:
mainbisection_2p_for_simulation.c and mainbisection_2p_for_single_dataset.c
The pdf file is obtainable from here. (Access to the file will depend on your entitlements.) In addition, the accepted post peer review version of manuscript is obtainable from here.
Last updated: 2013/11/18