Showing papers in "Statistics & Probability Letters in 2013"

TL;DR: In this paper, a stochastic SIRS epidemic model with general incidence rate in a population of varying size is studied and sufficient conditions for the extinction and the existence of a unique stationary distribution are obtained.

TL;DR: In this paper, the authors studied the convergence of a drift implicit scheme for one-dimensional SDEs that was considered by Alfonsi for the Cox-Ingersoll-Ross process.

TL;DR: This paper gives asymptotic results for a kNN generalized regression estimator when the observed variables take values in any abstract space and the main novelty is the uniform consistency result.

TL;DR: Tempered fractional Gaussian noise (TFGN) as discussed by the authors modifies the power law kernel in the moving average representation of a fractional Brownian motion, adding an exponential tempering.

TL;DR: In this article, the authors give asymptotically optimal tail estimates of the total variation distance between the empirical and the true distributions over countable sets for all p ∈ [ 0, 1 ] and illustrate a simple transition from the linear regime near the endpoints to the square root regime elsewhere.

TL;DR: In this paper, it was shown that the multivariate Rosenblatt distribution belongs to the Thorin class which is a subset of the class of self-decomposable distributions.

TL;DR: In this paper, a non-reversible Markov chain with a cycle on the corresponding graph is constructed by adding some antisymmetric perturbations to the original chain.

TL;DR: It is shown how the Samaniego signature can be computed more efficiently from the diagonal section of the reliability function via derivatives.

TL;DR: In this paper, two novel methods to estimate positive surveys from negative surveys are proposed, which can return nonnegative and proper values, and their results are identical, and simulation experiments demonstrate that the proposed two methods return more reasonable results than the traditional method.

TL;DR: In this paper, the moderate deviation principle for a class of point processes, namely linear Hawkes processes, was obtained for point processes with a fixed number of points in the system.

TL;DR: In this paper, a new class of skew distributions containing both unimodal as well as bimodal distributions with flexible hazard rate behavior is introduced, and several distributional properties of this class are investigated.

TL;DR: In this article, the authors introduced a quantile version of the entropy function in past lifetime and studied its properties, and proved characterizations theorems for some well known quantile lifetime distributions.

TL;DR: Using a connection between the rearrangement algorithm introduced in Puccetti and Ruschendorf (2012) and convex order, this article showed how to compute the best possible expected shortfall for the sum of d random variables having fixed marginal distributions.

TL;DR: In this paper, it was shown that λ ≥ ( ∏ i = 1 n λ i α ) 1 α implies that X 1 : n ≤ r h X 1: n ∗ for α > 1 and X 2 : n∗ for 0 α ≤ 1.

TL;DR: In this paper, the stationary distribution of the facultative population model with a degenerate noise was considered, and sufficient conditions were provided for the noise intensity matrix to be degenerate.

TL;DR: In this article, the same estimate holds true even when the coefficients have different signs, and the estimate is also improved by means of an empirical approximation error when the model fits the data well.

TL;DR: A dimension reduction method for model-based clustering via a finite mixture of shifted asymmetric Laplace distributions is introduced, based on existing work within the Gaussian paradigm and relies on identification of a reduced subspace.

TL;DR: The obtained results are used to derive asymptotic lower bounds of precise large deviations in a multi-risk model and extend and improve the related existing results substantially.

TL;DR: In this article, the authors prove large deviation principles for two versions of fractional Poisson processes: the main version is a renewal process, the alternative version is weighted Poisson process.

TL;DR: In this paper, the central limit theorem for the least squares estimator of the Ornstein-Uhlenbeck process was proved for the case of the unknown parameter θ > 0.

TL;DR: In this article, it was shown that if λ weakly majorizes μ then r n ≥ r n : n ( μ ; x ), ∀ x > 0, thereby strengthening the results of Dykstra et al.

TL;DR: In this article, a weak invariance principle was established for the normalized partial sum-process with two moments and a fairly general dependence structure, extending a recent result of Berkes et al..

TL;DR: The authors showed that at least seven parameters of interest to a social scientist can be estimated from a single sample and one response from each respondent from a real survey data application with a real-world application.

TL;DR: In this article, it was shown that the componentwise maxima of weakly dependent bivariate stationary Gaussian triangular arrays converge in distribution after appropriate normalization to Husler-Reiss distribution.

TL;DR: This paper computes the fractal dimensions of their process limits, which represent particle traces in anomalous diffusion, and estimates the waiting times between particle jumps in continuous time random walks.

TL;DR: In this paper, two methods for interval estimation based on an approximate generalized pivotal quantity and a fiducial quantity were proposed for the mean of lognormal distribution with excess zeros.

TL;DR: In this paper, a modified ranked set sampling (RSS) called moving-Extreme Ranked Set Sampling (MERSS) is considered for the estimation of the scale parameter of scale distributions.

TL;DR: In this article, a convex linear combination of multivariate Skew Normal mixtures can be represented as finite mixtures of univariate skew normal distributions, which can be used in modeling portfolio returns where the evaluation of extremal events is of great interest.

TL;DR: This article proposed an estimator based on the singular value decomposition of the third standardized cumulant, which is consistent when sampling from a mixture of symmetric, homoscedastic components with finite third moments and different weights.