this review provides the basic principle and rational for roc analysis of rating and continuous diagnostic test results versus a gold standard. derived indexes of accuracy, in particular area under the curve (auc) has a meaningful interpretation for disease classification from healthy subjects. the methods of estimate of auc and its testing in single diagnostic test and also comparative studies...

I SUMMARY. The object of the present investigation is to propose and study a class I of nonparametric tests for the multivariate analysis of variance (MANOVA) problem relating to complete two way layouts. In this context, the concept of rank-permuta-I I I .-tions for multidimensional interchangeability is developed, and the same is incorporated in the formulation of a class of genuinely distrib...

We develop two kernel smoothing based tests of a parametric mean-regression model against a nonparametric alternative when the response variable is rightcensored. The new test statistics are inspired by the synthetic data and the weighted least squares approaches for estimating the parameters of a (non)linear regression model under censoring. The asymptotic critical values of our tests are give...

This paper discusses some tests of lack-of-fit of a parametric regression model when errors form a long memory moving average process with the long memory parameter 0 < d < 1/2, and when design is non-random and uniform on [0, 1]. These tests are based on certain minimized distances between a nonparametric regression function estimator and the parametric model being fitted. The paper investigat...

Several new tests are proposed for examining the adequacy of a family of parametric models against large nonparametric alternatives. These tests formally check if the bias vector of residuals from parametric Ž ts is negligible by using the adaptive Neyman test and other methods. The testing procedures formalize the traditional model diagnostic tools based on residual plots. We examine the rates...

We carry out a nonparametric analysis of financial durations. We make use of an existing algorithm to describe nonparametrically the dynamics of the process in terms of its lagged realizations and of a latent variable, its conditional mean. The devices needed to effectively apply the algorithm to our dataset are presented. On simulated data, the nonparametric procedure yields better estimates t...

We propose tests for sphericity and identity of high-dimensional covariance matrices. The tests are nonparametric without assuming a specific parametric distribution for the data. They can accommodate situations where the data dimension is much larger than the sample size, namely the “large p, small n” situations. We demonstrate by both theoretical and empirical studies that the tests have good...