This paper focuses on the problem of testing the null hypothesis that the variance functions of two populations are equal versus one-sided alternatives under a general nonparametric heteroscedastic regression ...
Modern science frequently involves the analysis of large amount of quantitative information and the simultaneous testing of thousands or even hundreds of thousands null hypotheses. In this context, sometimes, ...
... coefficients, thus avoiding testing bias. Results: Family data across three generations, including 123 colorectal cancers, were analyzed. When compared with the first generation, the crude HR for anticipation ...
Background: Current HIV treatment guidelines recommend antiretroviral treatment (ART) initiation for all HIV-infected individuals regardless of CD4 count. This study evaluates the immunological and virological ...
... of testing the null hypothesis that the marginal distributions of p variables are the same for two groups. We propose a test statistic motivated by the simple idea of comparing, for each of the p variables, ...
... any given specification of arbitrary order and may even be invoked for testing not just GARCH models but also some related models such as autoregressive conditional duration models. The test statistic ...
... coefficients, thus avoiding testing bias.
Results: Family data across three generations, including 123 colorectal cancers, were analyzed. When compared with the first generation, the crude HR for anticipation ...
Several aquatic living resources are overexploited. An example of this is a barnacle fishery, which is a commercial species that commands high prices in the market. We feel that not enough is known about ...
In certain settings, such as microarray data, the sampling information is formed by a large number of possibly dependent small data sets. In special applications, for example in order to perform clustering, ...
In practice, count data exhibit over-dispersion, zero-inflation and even heavy tails. The Poisson–Tweedie distribution is a flexible parametric family able to accommodate these features. This paper proposes ...
The problem of testing for the parametric form of the conditional variance is considered
in a fully nonparametric regression model. A test statistic based on a weighted
L2-distance between the empirical ...
... of testing that the innovation distribution of a multivariate GARCH model is Gaussian. We study the finite-sample behavior of the new tests, compare the criteria with alternative existing procedures, and ...
... as well as in the context of testing that the innovation distribution of a multivariate GARCH model is Gaussian. We also study the finite-sample behavior of the new tests and compare the new criteria with ...
A class of tests for testing independence whose test statistic is an -norm of the difference between the joint empirical characteristic function and the product of the marginal empirical characteristic ...
... power of the resulting test are evaluated by means of a simulation study. The procedure can be extended to testing for the equality of d>2 error distributions. ...
Assessment of the diagnostic accuracy of biomarkers through receiver operating characteristic curve analysis frequently involves a limit of detection imposed by the laboratory analytical system precision. ...
In the last decades, multiple-testing problems have received much attention. Many different methods have been proposed in order to deal with this relevant issue. Most of them are focused on controlling ...
... this article, we introduce a novel transformation of this difference that leads to ADF tests with well-known critical values. The general methodology is illustrated with applications to testing for parametric ...
... of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional ...
Several procedures have been proposed for testing goodness-of-fit to the error distribution in nonparametric regression models. The null distribution of the associated test statistics is usually approximated ...
... kernel smoothing for variable selection in functional data and a wavelet-based weighted LASSO functional linear regression. Our approach proved to have some advantages over these two testing approaches, ...
Several procedures have been proposed for testing the equality of error distributions in two or more nonparametric regression models. Here we deal with methods based on comparing estimators of the cumulative ...
The sequential goodness-of-fit (SGoF) multiple testing method has recently been proposed as an alternative to the familywise error rate-And the false discovery rate-controlling procedures in high-dimensional ...
... cloud. Also bootstrap-based procedures are proposed for testing a null hypothesis establishing that the surface has planar symmetry. After checking the validity of the proposed methodology with simulated ...
... Finally, we provide an application to the problem of testing for separate families of distributions. All applications are illustrated with numerical examples. ...
We propose a method to evaluate the existence of spatial variability in the covariance structure in a geographically weighted principal components analysis (GWPCA). The method, that is extensive to locally ...
Receiver operating characteristic (ROC) curves are useful statistical tools for medi-
cal diagnostic testing. It has been proved its capability to assess diagnostic marker’s
ability to distinguish between ...
... the 2D, 3D or nn-D space and the multinomial distribution the statistical approach for testing homogeneity. A simulation method is proposed in order to analyze the applied performance of this idea. ...
... that is to say, testing goodness-of-fit for the symmetric component. This work proposes a test of such hypothesis. Taking into account that the normal law is perhaps the most studied distribution, as a ...
... additive models for the ROC curve (ROC-GAM). The main aim of the paper is to offer new inferential procedures for testing the effect of covariates over the conditional ROC curve within the ROC-GAM context. ...
The problem of testing the null hypothesis that the regression functions of two populations are equal versus one-sided alternatives under a general nonparametric homoscedastic regression model is considered. ...
... transition probabilities and related curves are available, including the Markov information in the construction of the estimators allows for variance reduction. Therefore, testing for the Markov condition ...
... method, which is a method of high interest when one aims to increase the statistical power in a multiple testing scenario. The adjusted p-value is the smallest level at which the SGoF procedure would still ...
Beta-binomial sequential goodness-of-fit (or BB-SGoF) method for multiple
testing has been recently proposed as a suitable modification of the sequential
goodness-of-fit (SGoF) multiple testingmethod ...
The sequential goodness-of-fit (SGoF) multiple testing method has recently been proposed as an alternative to the familywise error rate- and the false discovery rate-controlling procedures in highdimensional ...
In this paper we present a new R package called sgof for multiple hypothesis testing. The principal aim of this package is to implement SGoF-type multiple testing methods, known to be more powerful than ...
... procedures are proposed for testing the null hypothesis. In order to validate the methodology a simulated study was conducted. Finally, the proposed methodology was applied to the inspection of a parabolic ...
... fails in some applications, leading to inconsistent estimates. In this paper, we provide a new approach for testing Markovianity in the illness-death model. The new method is based on measuring the future–past ...
... through the Aalen-Johansen estimator. However, Aalen-Johansen may be biased when the underlying process is not Markov. In this paper, we provide a new approach for testing Markovianity in the three-stat ...
... on hypothesis testing. The results reveal that our methodology reduces the number of significant variables by approximately 50% and that both forestry and GPS-signal-related variables are significant. ...
When working with high-dimensional biological data the so-called multiple hypothesis testing problem emerges. That is, when many separate tests are performed, several will be significant by chance provoking ...
... the derivative curves, and binning techniques were applied to speed up computation in the estimation and testing processes. The software is illustrated using biological data. ...
... mean, but also on the variance of the diagnostic test. We also present a bootstrap-based method for testing for a significant covariate effect on the ROC curve. To illustrate the method, endocrine data ...
... were applied to speed up computation in the estimation and testing processes. A simulation study was conducted to assess the validity of these bootstrap‐based tests. This methodology was applied to study ...
... the derivative curves, and binning techniques were applied to speed up computation in the estimation and testing processes. The software is illustrated using biological data. ...