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 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 ...
... established the asymptotic normality of the ISE and HD for the proposed estimators. In addition, the uniformly strongly consistency of the new kernel estimator of the density is discussed. Also, a simulation ...
... the asymptotic normality of the proposed estimators when the observations are assumed to be a stationary α-mixing sequence. Finite sample behavior of the estimators is investigated via simulations too. ...
... the empirical characteristic functions computed from the two samples. The asymptotic normality of the test statistic is derived under mixing conditions. In our asymptotic analysis the number of variables ...
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 ...
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 ...
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 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 ...
... stationary α-mixing sequence, we derive weak convergence with a certain rate and prove asymptotic normality of the weighted estimator. The asymptotic normality shows that the weighted estimator preserves ...
Two-tailed asymptotic inferences for the difference d = p2 − p1 with independent proportions have been widely studied in the literature. Nevertheless, the case of one tail has received less attention, ...
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 ...
... estimator of the unknown parameter. Under suitable assumptions, we investigate the asymptotic normality of the proposed estimators and prove the EL ratio statistics has a standard chi-squared limiting ...
... time, the asymptotic normality of the maximum EL and PEL estimators of the parameter is established. Also, the variable selection of the model in the presence and absence of auxiliary information, respectively, ...
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 ...
Nonparametric estimation of the transition probability matrix of a progressive multi-state model is consideredunder cross-sectional sampling. Two diﬀerent estimators adapted to possibly right-censored ...
... the variable selection of the covariates in the linear part by adopting adaptive LASSO penalty. Under appropriate assumptions, the asymptotic normality of the proposed estimators is established, and the ...
... further, we define a plug-in weighted estimator of the conditional hazard rate. Under strong mixing assumptions, we derive asymptotic normality of the proposed estimators which permit to built a confidence ...
This paper addresses the problem of hypothesis test on response mean with various inequality constraints in the presence of covariates when response data are missing at random. The various hypotheses include ...
... -mixing sequence, we prove that the proposed estimators and Jackknife empirical likelihood statistic are asymptotic normality and asymptotic distribution, respectively. Numerical simulations are carried ...
... squared error (MISE). Unlike for kernel estimator, the MISE expression of the estimator is not affected by the presence of discontinuities in the curve. Meanwhile, asymptotic normality of the estimator ...
In Survival Analysis and related fields of research right-censored and left-truncated data often appear. Usually, it is assumed that the right-censoring variable is independent of the lifetime of ultimate ...
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 ...
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 ...
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 ...
In statistics it is customary to realize asymptotic inferences about the difference d, the ratio R or a linear combination L of two independent proportions. In this article the authors evaluate ten inference ...
... factors. A distinctive feature of our estimator is that it does not require a fully parametric model for the conditional mean and variance. We establish consistency and asymptotic normality of the estimates. ...
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 ...
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 ...
In order to investigate the convergence rate of the asymptotic normality for the estimator of the conditional mode function for the left-truncation model, we derive a Berry–Esseen type bound of the estimator ...
Based on the idea of the local polynomial smoother, we construct the Nadaraya–Watson type and local linear estimators of conditional density function for a left-truncation model. Asymptotic normality of ...
A test approach to the model selection problem based on characteristic functions (CFs) is proposed. The scheme is close to that proposed by Vuong (Econometrica 57:257–306, 1989), which is based on comparing ...
Two-sided asymptotic confidence intervals for an unknown proportion p have been the subject of a great deal of literature. Surprisingly, there are very few papers devoted, like this article, to the case ...
Yu et al. [An improved score interval with a modified midpoint for a binomial proportion. J Stat Comput Simul. 2014;84:1022–1038] propose a novel confidence interval (CI) for a binomial proportion by modifying ...
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. ...
Presmoothed Kaplan–Meier integrals have been proposed as suitable estimators in semiparametric censorship models. They are based on a modification of Kaplan–Meier weights which replaces the censoring indicators ...
Nonparametric regression with a doubly truncated response is introduced. Local constant and local linear kernel-type estimators are proposed. Asymptotic expressions for the bias and the variance of the ...
... the lifetime observations with covariates form a stationary ˛-mixing sequence. Asymptotic normality of the estimators is established.
Finite sample behaviour of the estimators is investigated via simulations. ...
Multi-state models are often used for modeling complex event history data. In these models the estimation of the transition probabilities is of particular interest, since they allow for long-term predictions ...
A class of goodness-of-fit tests of the Cramer-von Mises type is considered. More specifically, the test statistic of each test is an L-2-norm of the difference between the empirical characteristic function ...
In this paper we are interested in checking whether the conditional variances are equal in k >= 2 location-scale regression models. Our procedure is fully nonparametric and is based on the comparison of ...
This article studies a new procedure to test for the equality of k regression curves in a fully non-parametric context. The test is based on the comparison of empirical estimators of the characteristic ...
A class of goodness-of-fit tests whose test statistic is an L-2 norm of the difference of the empirical characteristic function of the sample and a parametric estimate of the characteristic function in ...
In this paper a copula-graphic estimator is proposed for left-truncated and right-censored survival data. It is assumed that there is some dependent censoring acting on the variable of interest, which ...
In this paper, a copula-graphic estimator is proposed for censored survival data. It is assumed that there is some dependent censoring acting on the variable of interest that may come from an existing ...