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In data-processing standpoint, an efficient algorithm for identifying the minimum value among a set of measurements are record statistics. From a sequence of n independent identically distributed continuous random variables only about log(n) records are expected, so we expect to have little data, hence any prior information is welcome (Houchens, Record value theory and inference, Ph.D. thesis, University...
We consider testing nonparametric hypotheses against ordered alternatives and propose a new unified approach for dependent and independent samples and factorial designs. The new approach allows for arbitrary underlying distributions, including quantitative and discrete ordinal (ordered categorical), or even binary data. It is compared to procedures available in the literature and applied to different...
In this paper, the problem of estimating the precision matrix of a multivariate Pearson type II-model is considered. A new class of estimators is proposed. Moreover, the risk functions of the usual and the proposed estimators are explicitly derived. It is shown that the proposed estimator dominates the MLE and the unbiased estimator, under the quadratic loss function. A simulation study is carried...
Experimental designs for field experiments are useful in planning agricultural experiments, environmental studies, etc. Optimal designs depend on the spatial correlation structures of field plots. Without knowing the correlation structures exactly in practice, we can study robust designs. Various neighborhoods of covariance matrices are introduced and discussed. Minimax robust design criteria are...
In the present work we develop a randomized two-treatment adaptive allocation design with covariates ensuring smaller variability of treatment allocations. We study, both numerically and theoretically, several exact and limiting properties of the design and consider an inferential problem following the allocation design. We compare the design with some of the existing allocation designs by computing...
Suppose that the longitudinal observations (Yij, Xij, tij) for i = 1, . . . ,n; j = 1, . . . ,mi are modeled by the semiparamtric model $${Y_{ij}=X_{ij}^{T}\beta_{0}+g(t_{ij})+e_{ij},}$$ where β0 is a k × 1 vector of unknown parameters, g(·) is an unknown estimated function and eij are unobserved disturbances. This article consider M-type regressions which include mean, median...
Motivated by open problems of well posedness in fluid dynamics, two topics related to strong solutions of SDEs are discussed. The first one on stochastic flows for SDEs with non regular drift helps to solve a stochastic transport equation where the corresponding deterministic equation is not well posed. The second one is a concept of strong superposition solution motivated by problems where uniqueness...
We consider the classical problem of nonparametrically estimating a star-shaped distribution, i.e., a distribution function F on [0,∞) with the property that F(u)/u is nondecreasing on the set {u : F(u) < 1}. This problem is intriguing because of the fact that a well defined maximum likelihood estimator (MLE) exists, but this MLE is inconsistent. In this paper, we argue that the likelihood that...
As well as arising naturally in the study of non-intersecting random paths, random spanning trees, and eigenvalues of random matrices, determinantal point processes (sometimes also called fermionic point processes) are relatively easy to simulate and provide a quite broad class of models that exhibit repulsion between points. The fundamental ingredient used to construct a determinantal point process...
This work presents intensity-based credit risk models where the default intensity of the point process is modeled by an Ornstein-Uhlenbeck type process completely driven by jumps. Under this model we compute the default probability over time by linking it to the characteristic function of the integrated intensity process. In case of the Gamma and the Inverse Gaussian Ornstein-Uhlenbeck processes this...
We study the local times of fractional Brownian motions for all temporal dimensions, N, spatial dimensions d and Hurst parameters H for which local times exist. We establish a Hölder continuity result that is a refinement of Xiao (Probab Th Rel Fields 109:129–157, 1997). Our approach is an adaptation of the more general attack of Xiao (Probab Th Rel Fields 109:129–157, 1997) using ideas of Baraka...
We consider n × n real symmetric random matrices n−1/2W with independent (modulo symmetry condition) entries and the (null) sample covariance matrices n−1ATA with independent entries of m × n matrix A. Assuming first that the 4th cumulant (excess) κ4 of entries of W and A is zero and that their 4th moments satisfy a Lindeberg type condition, we prove that linear statistics of eigenvalues...
The paper is devoted to recall weak dependence conditions from Dedecker et al. (Weak dependence, examples and applications. Lecture Notes in Statistics, vol 190, 2007)’s monograph; the main basic results are recalled here and we go further in some new applications. We develop here several models of weakly dependent processes and random fields. Among them an ARCH(∞) model is considered with statistical...
In algebraic statistics, computational techniques from algebraic geometry become tools to address statistical problems. This, in turn, may prompt research in algebraic geometry. The basic ideas at the core of algebraic statistics will be presented. In particular, we shall consider application to contingency tables and to design of experiments.
This paper considers multiple regression procedures for analyzing the relationship between a response variable and a vector of d covariates in a nonparametric setting where tuning parameters need to be selected. We introduce an approach which handles the dilemma that with high dimensional data the sparsity of data in regions of the sample space makes estimation of nonparametric curves and surfaces...
Many models to analyze incomplete data that allow the missingness to be non-random have been developed. Since such models necessarily rely on unverifiable assumptions, considerable research nowadays is devoted to assess the sensitivity of resulting inferences. A popular sensitivity route, next to local influence (Cook in J Roy Stat Soc Ser B 2:133–169, 1986; Jansen et al. in Biometrics 59:410–419,...
A reliability experimenter is often interested in studying the effects of extreme or varying stress factors such as load, pressure, temperature and voltage on the lifetimes of experimental units. Accelerated life-tests allow the experimenter to vary the levels of these stress factors in order to obtain information on the parameters of the lifetime distributions more rapidly than under normal operating...
We discuss a new method of estimation of parameters in semiparametric and nonparametric models. The method is based on U-statistics constructed from quadratic influence functions. The latter extend ordinary linear influence functions of the parameter of interest as defined in semiparametric theory, and represent second order derivatives of this parameter. For parameters for which the matching cannot...
Densities of functions of independent and identically distributed random observations can be estimated by a local U-statistic. It has been shown recently that, under an appropriate integrability condition, this estimator behaves asymptotically like an empirical estimator. In particular, it converges at the parametric rate. The integrability condition is rather restrictive. It fails for the sum of...
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