Related Experiment Video
Updated: May 20, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Closed-form estimators for the inverse Nakagami distribution
Victor Nawa1, Saralees Nadarajah2
1University of Zambia, Department of Mathematics and Statistics, P.O. Box 32379, Lusaka, Zambia.
Abstract:
The inverse Nakagami distribution due to Louzada et al. (2018) does not have closed-form maximum likelihood estimators. Closed-form estimators by adapting the method of moments are proposed in this note. Also proposed is a bias corrected version of the estimators. Large sample properties including asymptotic variances of the proposed estimators are derived. A simulation study and data applications are provided to compare the performances of the maximum likelihood estimators, the proposed estimators and their bias corrected versions.
Related Concept Videos
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Distributions to Estimate Population Parameter
Estimating Population Mean with Unknown Standard Deviation
William S. Gosset (1876–1937) of the...
Estimating Population Mean with Known Standard Deviation
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
Kaplan-Meier Approach
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...

