Registry data typically report incident cases within a certain calendar time interval. Such interval sampling induces double truncation on the incidence times, which may result in an observational bias. ...
This paper addresses interactive one-machine sequencing situations in which the costs of processing a job are given by an exponential function of its completion time. The main difference with the standard ...
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 ...
We analyze the utility of multiscale supervised classification algorithms for object detection and extraction from laser scanning or photogrammetric point clouds. Only the geometric information (the point ...
In this paper, we consider a general regression model where missing data occur in the response and in the covariates. Our aim is to estimate the marginal distribution function and a marginal functional, ...
We consider a goodness-of-fit test for certain parametrizations of conditionally heteroscedastic time series with unobserved components. Our test is quite general in that it can be employed to validate ...
The one-parameter Bell family of distributions, introduced by Castellares et al. (Appl Math Model 56:172–185, 2018), is useful for modeling count data. This paper proposes and studies a goodness-of-fit ...
The use of the area under the receiver-operating characteristic, ROC, curve (AUC) as an index of diagnostic accuracy is overwhelming in fields such as biomedical science and machine learning. It seems ...
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, ...
The paper first introduces a new two-parameter continuous probability distribution
with bounded support from the extended exponential-geometric distribution. Closed-
form expressions are given for the ...
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 ...
We generalize a recent class of tests for univariate normality that are based on the empirical moment generating function to the multivariate setting, thus obtaining a class of affine invariant, consistent ...
We provide novel characterizations of multivariate normality that incorporate both the characteristic function and the moment generating function, and we employ these results to construct a class of affine ...
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 ...
A test for the equality of error distributions in two nonparametric regression models is proposed. The test statistic is based on comparing the empirical characteristic functions of the residuals calculated ...
Auxiliary information x is commonly used in survey sampling at the estimation
stage. We propose an estimator of the finite population distribution function
Fy(t) when x is available for all units in ...
The aim of this study was to provide percentile curves and reference values for the performance in 2000-m maximal effort on rowing ergometer. A cross-sectional study was carried out with a non-probabilistic ...
This paper addresses interactive one-machine sequencing situations in which the costs of processinga job are given by an exponential function of its completion time. The main difference with thestandard ...
The purpose of this paper is two fold. First, we investigate estimation for varying coefficient partially linear models in which covariates in the nonparametric part are measured with errors. As there ...
In this paper, we study the linear quantile regression model when response data are missing at random. Based on the inverse probability weight method, we establish an estimation equation on quantile regression ...
Based on the inverse probability weight method, we, in this article, construct the empirical likelihood (EL) and penalized empirical likelihood (PEL) ratios of the parameter in the linear quantile regression ...
This paper focuses on the consequences of assuming a wrong model for multinomial data when using minimum penalized phi-divergence, also known as minimum penalized disparity estimators, to estimate the ...
This article proposes a new general methodology for constructing nonparametric and semiparametric Asymptotically Distribution-Free (ADF) tests for semiparametric hypotheses in regression models for possibly ...
The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, ...
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 ...
The NPMLE of a distribution function from doubly truncated data was introduced in the seminal paper of Efron and Petrosian. The consistency of the Efron-Petrosian estimator depends however on the assumption ...
Heavy metal pollution can result in the degradation of the soil, air and water bodies' quality affecting the health of all living organism. We analyze the spatial distribution of the concentrations of ...
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 ...
For the partially linear varying-coefficient model when the parametric covariates are measured with additive errors, the estimator of the error variance is defined based on residuals of the model. At the ...
We propose a generalization of simple games to partition function form games based on a monotonicity property that we define in this context. This property allows us to properly speak about minimal winning ...
In this work, some properties of the L2-deviations of the Nadaraya-Watson variogram estimators are analyzed, for both the anisotropic and the isotropic settings. Their convergence in distribution is established, ...
Goodness-of-fit tests for the innovation distribution in GARCH models based on measuring deviations between the empirical characteristic function of the residuals and the characteristic function under ...
Research question: The most common result in the analysis of efficiency in multisport competitions like the Olympic Games using the data envelopment analysis (DEA) is a ranking of the participating countries. ...
Meta-analyses, broadly defined as the quantitative review and synthesis of the results of related but independent comparable studies, allow to know the state of the art of one considered topic. Since the ...
The receiver operating characteristic curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous markers. It represents in a plot true-positive rates against ...
This paper studies properties of parameter estimators obtained by minimizing a distance between the empirical probability generating function and the probability generating function of a model for count ...
Muth introduced a probability distribution with application in reliability theory. We propose a new model from the Muth law. This paper studies its statistical properties, such as the computation of the ...
The problem of estimation of the shape parameter in a generalized half-logistic distribution for progressively type-II censored samples is of interest in reliability and survival analysis. In this paper, ...
A class of tests for the two-sample problem whose test statistic is an L2 norm of the difference of the empirical characteristic functions of the samples is considered. The null distribution can be estimated ...
A class of tests for the two-sample problem for count data whose test statistic is an
L2-norm of the difference between the empirical probability generating functions associated with each sample is considered. ...
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 ...
Tests are proposed for the assumption that the conditional distribution of a multivariate GARCH process is elliptic. These tests are of Kolmogorov–Smirnov and Cramér–von Mises-type and make use of the ...
Objectives: To analyze the survival of treatment lines with different biologics in a cohort of patients diagnosed with rheumatoid arthritis (RA), psoriatic arthritis (AP), ankylosing spondylitis (AS) and ...
Objectives: To analyze the reasons for discontinuation the biological treatment in a cohort of patients diagnosed with rheumatoid arthritis (RA), psoriatic arthritis (PA), ankylosing spondylitis (AS) and ...
For the high-dimensional partially linear varying coefficient models where covariates in the nonparametric part are measured with additive errors, we, in this paper, study asymptotic distributions of a ...
The evaluation of the spatial similarity of two observed point patterns is an important issue in spatial data quality assessment. In this work we propose a formal procedure that takes advantage of the ...
The Log-Lindley distribution is a continuous probability model with useful applications in insurance and inventory management. In this note, it is proven that pseudo-random data from this model can be ...
Many models of asymmetric distributions proposed in the statistical literature are obtained by transforming an arbitrary symmetric distribution by means of a skewing mechanism. In certain important cases, ...