Prediction based on linear combinations of order statistics and bivariate concomitants in the case of multivariate elliptical distributions
DOI10.1080/00949655.2012.739621zbMath1453.62500OpenAlexW2058815432MaRDI QIDQ5219966
Ahad Jamalizadeh, Rahman Farnoosh, Seyedeh Zahra Aghamohammadi, Narayanaswamy Balakrishnan
Publication date: 9 March 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2012.739621
predictionorder statisticsmixture distributionelliptical distributionconcomitantsmultivariate unified skew-elliptical distributionsquared-error loss
Multivariate distribution of statistics (62H10) Exact distribution theory in statistics (62E15) Order statistics; empirical distribution functions (62G30)
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Cites Work
- A Generalization of Shapiro–Wilk's Test for Multivariate Normality
- Concomitants of order statistics from multivariate elliptical distributions
- Regression analysis using order statistics
- A new test for multivariate normality
- Distributions of order statistics and linear combinations of order statistics from an elliptical distribution as mixtures of unified skew-elliptical distributions
- Concomitants of order statistics for dependent samples
- Modeling maxima of longitudinal contralateral observations
- Prediction in a trivariate normal distribution via a linear combination of order statistics
- Convergence of sample paths of normalized sums of induced order statistics
- Correlation Analysis of Extreme Observations from a Multivariate Normal Distribution
- Nonlinear regression in a trivariate elliptical distribution via a linear combination of order statistics
- On the Unification of Families of Skew-normal Distributions
- Regression via order statistics and their concomitants
- Correlation analysis of ordered symmetrically dependent observations and their concomitants of order statistics
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