Article
Licensed
Unlicensed
Requires Authentication
Determining the Parameters of a Multinomial Distribution: The Fiducial Approach
-
Hans-Dieter Heike
Published/Copyright:
March 15, 2010
Abstract
A procedure is derived for determining the values of the parameters of a multinomial distribution by means of the fiducial approach proposed by Fisher. By decomposing the involved probability (mass or density) functions, it is shown that the resulting fiducial distributions belong to the Dirichlet family.
Published Online: 2010-03-15
Published in Print: 2005-October
© Heldermann Verlag
You are currently not able to access this content.
You are currently not able to access this content.
Articles in the same Issue
- 2005 - The Jakob Bernoulli Year 350th Anniversary of Jakob's Birth and 300th Anniversary of Jakob's Death
- Six Sigma the “Breakthrough Management Strategy”?
- Determining the Parameters of a Multinomial Distribution: The Fiducial Approach
- Some Group Inspection Based Multi-Attribute Control Charts to Identify Process Deterioration
- On Cumulative Conforming Type of Control Charts for High Quality Processes Under Sampling Inspection
- Monitoring Process Mean and Process Variance Using Collani's Statistic
- Ratio of Logistic and Bessel Random Variables
- Weibull Extension of a Bivariate Exponential Regression Model
- Weighted Least Squares Estimators for a Change-Point
- A Note on the Appropriateness of Taguchi's Loss Function
- Acceptance Sampling Based on the Inverse Rayleigh Distribution
- An Alternative Simple Proof of a Result Useful in Reliability Shock Models
- Draft International Standard ISO/DIS 2210: Milk and Milk Products
Articles in the same Issue
- 2005 - The Jakob Bernoulli Year 350th Anniversary of Jakob's Birth and 300th Anniversary of Jakob's Death
- Six Sigma the “Breakthrough Management Strategy”?
- Determining the Parameters of a Multinomial Distribution: The Fiducial Approach
- Some Group Inspection Based Multi-Attribute Control Charts to Identify Process Deterioration
- On Cumulative Conforming Type of Control Charts for High Quality Processes Under Sampling Inspection
- Monitoring Process Mean and Process Variance Using Collani's Statistic
- Ratio of Logistic and Bessel Random Variables
- Weibull Extension of a Bivariate Exponential Regression Model
- Weighted Least Squares Estimators for a Change-Point
- A Note on the Appropriateness of Taguchi's Loss Function
- Acceptance Sampling Based on the Inverse Rayleigh Distribution
- An Alternative Simple Proof of a Result Useful in Reliability Shock Models
- Draft International Standard ISO/DIS 2210: Milk and Milk Products
