Rank order statistics for unequal samples.
Rank statistics approach in generalized bootstrap
Rank statistics for two-sample location and scale problem for rounded-off data
Rank Test for Testing Randomness of a Regression Coefficient in a Linear Regression Model.
Rank test of hypothesis of randomness against a group of regression alternatives
Rank tests for scale: Hájek's influence and recent developments
Rank Tests for the 2 X 2 Split Pilot Design.
Rank tests for the hypotheses concerning unidentifiable objects
Rank tests in regression model based on minimum distance estimates
In this paper a new rank test in a linear regression model is introduced. The test statistic is based on a certain minimum distance estimator, however, unlike classical rank tests in regression it is not a simple linear rank statistic. Its exact distribution under the null hypothesis is derived, and further, the asymptotic distribution both under the null hypothesis and the local alternative is investigated. It is shown that the proposed test is applicable in measurement error models. Finally, a...
Rank tests of independence when samples are drawn from noncontinuous distributions or censored
Rank tests of symmetry and R-estimation of location parameter under measurement errors
This paper deals with the hypotheses of symmetry of distributions with respect to a location parameter when the response variables are subject to measurement errors. Rank tests of hypotheses about the location parameter and the related R-estimators are studied in an asymptotic set up. It is shown, when and under what conditions, these rank tests and R-estimators can be used effectively, and the effect of measurement errors on the power of the test and on the efficiency of the R-estimators is indicated....
Rank theory approach to ridge, LASSO, preliminary test and Stein-type estimators: Comparative study
In the development of efficient predictive models, the key is to identify suitable predictors for a given linear model. For the first time, this paper provides a comparative study of ridge regression, LASSO, preliminary test and Stein-type estimators based on the theory of rank statistics. Under the orthonormal design matrix of a given linear model, we find that the rank based ridge estimator outperforms the usual rank estimator, restricted R-estimator, rank-based LASSO, preliminary test and Stein-type...
Ranking and selection procedures for location parameter case based on -estimates
In this paper properties of some ranking and selection procedures based on robust -estimates of location parameter are studied. The least favorable configuration of parameters and the asymptotic efficiency relative to procedures based on sample means are found.
Ranking of Banks in Serbia
Rapid Emergence of Co-colonization with Community-acquired and Hospital-Acquired Methicillin-Resistant Staphylococcus aureus Strains in the Hospital Setting
Background: Community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA), a novel strain of MRSA, has recently emerged and rapidly spread in the community. Invasion into the hospital setting with replacement of the hospital-acquired MRSA (HA-MRSA) has also been documented. Co-colonization with both CA-MRSA and HA-MRSA would have important clinical implications given differences in antimicrobial susceptibility profiles and the potential...
Rate of convergence for a class of RCA estimators
This work deals with Random Coefficient Autoregressive models where the error process is a martingale difference sequence. A class of estimators of unknown parameter is employed. This class was originally proposed by Schick and it covers both least squares estimator and maximum likelihood estimator for instance. Asymptotic behavior of such estimators is explored, especially the rate of convergence to normal distribution is established.
Rate of Convergence in the Central Limit Theorem and in the Strong Law of Large Numbers for von Mises Statistics.
Rate of Convergence to Normality for U-Statistics with Kernel of Arbitrary Degree.
Rates of Convergence for the Distance Between Distribution Function Estimators.
Rates of strong uniform consistency for multivariate kernel density estimators