Estimation in one–way classification with heteroscedastic error
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Publication:3798080
DOI10.1080/02331888708802014zbMath0652.62065OpenAlexW1967147385MaRDI QIDQ3798080
Publication date: 1987
Published in: Unnamed Author (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888708802014
heteroscedasticityvariancerandom effect modelBAN estimatefixed effect parameterunbalanced one way classification
Asymptotic properties of parametric estimators (62F12) Point estimation (62F10) Analysis of variance and covariance (ANOVA) (62J10)
Cites Work
- Estimation of variance components in an unbalanced one-way classification
- Robust estimation in heteroscedastic linear models
- Using residuals robustly I: Tests for heteroscedasticity, nonlinearity
- Estimation for a linear regression model with unknown diagonal covariance matrix
- Asymptotic properties of maximum likelihood estimates in the mixed model of the analysis of variance
- Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
- A Comparison Between Maximum Likelihood and Generalized Least Squares in a Heteroscedastic Linear Model
- Least Squares Estimation when the Covariance Matrix and Parameter Vector are Functionally Related
- Estimators for the One-Way Random Effects Model with Unequal Error Variances
- Correcting Inhomogeneity of Variance with Power Transformation Weighting
- Asymptotic Properties of Maximum Likelihood Estimators in Some Nonstandard Cases, II
- Asymptotic Properties of Non-Linear Least Squares Estimators
- Consistent Estimates Based on Partially Consistent Observations
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