Back to Search
Start Over
A note on weighted least square distribution fitting and full standardization of the empirical distribution function
- Source :
- TEST. 27:946-967
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- The relationship between the norm square of the standardized cumulative distribution and the chi-square statistic is examined using the form of the covariance matrix as well as the projection perspective. This investigation enables us to give uncorrelated components of the chi-square statistic and to provide interpretation of these components as innovations standardizing the cumulative distribution values. The norm square of the standardized difference between empirical and theoretical cumulative distributions is also examined as an objective function for parameter estimation. Its relationship to the chi-square distance enables us to discuss the large sample properties of these estimators and a difference in their properties in the cases that the distribution is evaluated at fixed and random points.
- Subjects :
- Statistics and Probability
Covariance matrix
Estimation theory
Cumulative distribution function
Estimator
010103 numerical & computational mathematics
01 natural sciences
Empirical distribution function
Distribution fitting
Square (algebra)
010104 statistics & probability
weighted least squares
minimum chi-square
empirical distribution
distribution fitting
Statistics
0101 mathematics
Statistics, Probability and Uncertainty
Statistic
Mathematics
Subjects
Details
- ISSN :
- 18638260 and 11330686
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- TEST
- Accession number :
- edsair.doi.dedup.....1cc68b8d904ad2023eded67766192b9c
- Full Text :
- https://doi.org/10.1007/s11749-018-0578-2