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A reversed-hazard-based nonlinear model for one-way classification.
- Source :
-
Communications in Statistics: Simulation & Computation . 2023, Vol. 52 Issue 9, p4378-4391. 14p. - Publication Year :
- 2023
-
Abstract
- This paper proposes a new statistical method for one-way classification which is based on the (reversed) hazard function of the response variable. The model parameters are estimated according the maximum likelihood approach. Several testing procedures, e.g., generalized likelihood ratio test, are investigated to assess homogeneity of populations. A non-parametric method for data analysis is also proposed. Two data sets are studied using the obtained results. [ABSTRACT FROM AUTHOR]
- Subjects :
- *LIKELIHOOD ratio tests
*CLASSIFICATION
*HAZARD function (Statistics)
Subjects
Details
- Language :
- English
- ISSN :
- 03610918
- Volume :
- 52
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- Communications in Statistics: Simulation & Computation
- Publication Type :
- Academic Journal
- Accession number :
- 172840256
- Full Text :
- https://doi.org/10.1080/03610918.2021.1962346