According to the IFCC, to determine the population-based reference interval (RI) of a test, 120 reference individuals are required. However, for some age groups such as newborns and preterm babies, it is difficult to obtain enough reference individuals. In this study, we consider both parametric and nonparametric bootstrap methods for estimating RIs and the associated confidence intervals (CIs)...

In this paper, we consider the goodness-of-fit for checking whether the nonparametric function in a partial linear regression model with missing covariate at random is a parametric one or not. We estimate the selection probability by using parametric and nonparametric approaches. Two score type tests are constructed with the estimated selection probability. The asymptotic distributions of the t...

In this paper, we focus on the experimental analysis on the performance in cluster analysis with the use of nonparametric tests on the clustering task. Particularly, we have studied whether the sample of results from multiple trials obtained by conventional clustering algorithms checks the necessary conditions for being analyzed through parametrical tests. The study is conducted by considering ...

Receiver operating characteristic (ROC) analysis, which yields indices of accuracy such as the area under the curve (AUC), is increasingly being used to evaluate the performances of diagnostic tests that produce results on continuous scales. Both parametric and nonparametric ROC approaches are available to assess the discriminant capacity of such tests, but there are no clear guidelines as to t...

Spectral analysis considers the problem of determining (the art of recovering) the spectral content (i.e., the distribution of power over frequency) of a stationary time series from a finite set of measurements, by means of either nonparametric or parametric techniques. This paper introduces the spectral analysis problem, motivates the definition of power spectral density functions, and reviews...

This paper discusses the problem of fitting a parametric model to the nonparametric component in partially linear regression models when covariates in parametric and nonparametric parts are subject to Berkson measurement errors. The proposed test is based on the supremum of a martingale transform of a certain partial sum process of calibrated residuals. Asymptotic null distribution of this tran...

This paper considers a class of nonparametric autoregression models with nonstationarity in the mean and then a class of nonparametric time series regression models with nonstationarity in both the conditional mean and conditional variance. For the nonparametric autoregression case, we propose a nonparametric unit–root test for the conditional mean. For the nonparametric time series regression ...