Statisticians are Fairly Robust Estimators of Location
Article Properties
-
LanguageEnglish
-
DOI (url)
-
Publication Date1977/03/01
-
Indian UGC (journal)
-
Refrences8
-
Citations23
-
Daniel A. Relles
-
William H. Rogers
Cite
Relles, Daniel A., and William H. Rogers. “Statisticians Are Fairly Robust Estimators of Location”. Journal of the American Statistical Association, vol. 72, no. 357, 1977, pp. 107-11, https://doi.org/10.1080/01621459.1977.10479918.
Relles, D. A., & Rogers, W. H. (1977). Statisticians are Fairly Robust Estimators of Location. Journal of the American Statistical Association, 72(357), 107-111. https://doi.org/10.1080/01621459.1977.10479918
Relles, Daniel A., and William H. Rogers. “Statisticians Are Fairly Robust Estimators of Location”. Journal of the American Statistical Association 72, no. 357 (1977): 107-11. https://doi.org/10.1080/01621459.1977.10479918.
Relles DA, Rogers WH. Statisticians are Fairly Robust Estimators of Location. Journal of the American Statistical Association. 1977;72(357):107-11.
Journal Categories
Science
Mathematics
Science
Mathematics
Probabilities
Mathematical statistics
You May Also Like
- Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
- Regularization and Variable Selection Via the Elastic Net
- Regression Shrinkage and Selection Via the Lasso
- Extended BIC for small-n-large-P sparse GLM
- Estimation and variable selection for semiparametric additive partial linear models
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Topics in the Investigation of Linear Relations Fitted by the Method of Least Squares | Journal of the Royal Statistical Society Series B: Statistical Methodology |
| 27 | 1967 |
| Topics in the Investigation of Linear Relations Fitted by the Method of Least Squares | 1973 | |||
| Robust Estimates of Location | 1972 | |||
| “Optimal Invariant Estimation of Location for Three Distributions and the Invariant Efficiency of Some Other Estimators,” | 1971 | |||
| Variance Reduction Techniques for Monte Carlo Sampling from Student Distributions | Technometrics |
| 1970 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Income, education, and other poverty-related variables: A journey through Bayesian hierarchical models | Heliyon | 2024 | ||
| A Bayesian Regression Model for the Non-standardized t Distribution with Location, Scale and Degrees of Freedom Parameters | Sankhya B |
| 2022 | |
| A new multivariate t distribution with variant tail weights and its application in robust regression analysis | Journal of Applied Statistics |
| 2021 | |
| Bayesian Estimation for the Extended t-process Regression Models with Independent Errors | Communications in Mathematics and Statistics |
| 2019 | |
| Robust FIR State Estimation of Dynamic Processes Corrupted by Outliers | IEEE Transactions on Industrial Informatics |
| 2019 |
Citations Analysis
The category
Science: Mathematics: Probabilities. Mathematical statistics 12
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled EXAMINATION OF REGRESSION RESIDUALS and was published in 1979. The most recent citation comes from a 2024 study titled Income, education, and other poverty-related variables: A journey through Bayesian hierarchical models. This article reached its peak citation in 2019, with 2 citations. It has been cited in 20 different journals. Among related journals, the Sankhya B cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.