Some non-parametric tests for the k-sample problem

Non-parametric k-sample tests: Density functions vs distribution functions

In this paper we introduce some tests for the comparison of k samples based on kernel density estimators (KDE), and we develope the Double Minimum method as a new and useful procedure for the crucial problem of bandwidth selection. We study, via Monte Carlo simulations, the statistical power of the proposed tests, as well as the impact of the smoothing degree and the performance of the Double M...

SOME HOHPARAMETRIC TESTS FOR THE MULTIVARIATE SEVERAL SAMPLE LOCATION PROBlEM

the algorithm for solving the inverse numerical range problem

برد عددی ماتریس مربعی a را با w(a) نشان داده و به این صورت تعریف می کنیم w(a)={x8ax:x ?s1} ، که در آن s1 گوی واحد است. در سال 2009، راسل کاردن مساله برد عددی معکوس را به این صورت مطرح کرده است : برای نقطه z?w(a)، بردار x?s1 را به گونه ای می یابیم که z=x*ax، در این پایان نامه ، الگوریتمی برای حل مساله برد عددی معکوس ارانه می دهیم.

Tests for mean vectors with two-step monotone missing data for the k-sample problem

We continue our recent work on the problem of testing the equality of two normal mean vectors when the data have two-step monotone pattern missing observations. This paper extends the two-sample problem in our previous paper to the k-sample problem. Under the assumption that the population covariance matrices are equal, we obtain the likelihood ratio test statistic for testing the hypothesis H0...

K-Sample Anderson-Darling Tests

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your perso...