Score and Wald tests for the homogeneity of inverse Gaussian scale parameters based on computational approach test
From MaRDI portal
Publication:5055159
DOI10.1080/03610918.2020.1811330OpenAlexW3082179525MaRDI QIDQ5055159
Fikri Gökpınar, Gamze Güven, Hatice Şamkar
Publication date: 13 December 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2020.1811330
inverse Gaussian distributionWald statisticscale parameterscore statisticcomputational approach test
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Testing homogeneity of inverse Gaussian scale-like parameters: a saddlepoint approach
- A note on testing homogeneity of the scale parameters of several inverse Gaussian distributions
- Testing the homogeneity of inverse Gaussian scale-like parameters
- The inverse Gaussian distribution. Statistical theory and applications
- Accelerated test models with the inverse Gaussian distribution
- The inverse Gaussian models: Analogues of symmetry, skewness and kurtosis
- Testing equality of scale parameters of two Weibull distributions in the presence of unequal shape parameters
- Cumulative Damage Models for System Failure with Application to Carbon Fibers and Composites
- Statistical Properties of Inverse Gaussian Distributions. I
- A Characterization of the Inverse Gaussian Distribution
- Prediction Limits for the Inverse Gaussian Distribution
- The Inverse Gaussian Distribution as a Lifetime Model
- ANALYSIS OF VARIANCE IN EXPERIMENTAL DESIGN WITH NONNORMAL ERROR DISTRIBUTIONS
- A SIMULATION STUDY ON TESTS FOR ONE-WAY ANOVA UNDER THE UNEQUAL VARIANCE ASSUMPTION
- A fiducial-based approach to the one-way ANOVA in the presence of nonnormality and heterogeneous error variances
- A Parametric Bootstrap Approach for One-Way ANOVA Under Unequal Variances with Unbalanced Data
- Testing Homogeneity of Inverse Gaussian Scale Parameters Based on Generalized Likelihood Ratio
- Models for Variable-Stress Accelerated Life Testing Experiments Based on Wiener Processes and the Inverse Gaussian Distribution