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Activity Number:
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622
- Probability Distribution Theory and Their Applications
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Type:
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Contributed
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Date/Time:
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Thursday, August 3, 2017 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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Abstract #322768
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Title:
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Parameter Inference for a Three-Parameter Generalized Birnbaum- Saunders Distribution
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Author(s):
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Naijun Sha*
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Companies:
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University of Texas At El Paso
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Keywords:
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Birnbaum-Saunders distribution ;
generalization ;
likelihood ;
Fisher's information ;
estimation ;
approximation
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Abstract:
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We present statistical inference methods for a generalized Birnbaum-Saunders (GBS) distribution. Some interesting properties of this highly flexible distribution are studied and presented. We explore further the likelihood-based approach and derive the Fisher information matrix. Based on an approximation method, we propose a new inference approach for the GBS distribution. Simulation studies are carried out to assess performance of the methods under various settings of parameter values with different sample sizes. Real data are analyzed for illustrative purpose to demonstrate the efficiency of the proposed method.
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Authors who are presenting talks have a * after their name.
