Showing papers in "Journal of Statistical Planning and Inference in 2011"

TL;DR: In this article, the authors investigated the effect of mis-specification on the prediction of product's MTTF (mean-time-to-failure) when the degradation model is wrongly fitted.

TL;DR: In this article, the theoretical properties of the maximum composite likelihood estimate (MCLE) are investigated in more detail, and the robustness of consistency of the MCLE is clarified and illustrated through some simple examples.

TL;DR: In this paper, the authors showed that the hazard rate of a series (parallel) system consisting of components with lifetimes is Schur concave (convex) with respect to the vector λ, if x 2 r (x) (x 2 r ˜ (x ) ) is decreasing (increasing).

TL;DR: In this paper, a nonconcave penalized least squares method is proposed to estimate both the parameters and the link function of the single index model, which can estimate parameters and select variables simultaneously.

TL;DR: In this paper, the run length properties of a CUSUM chart for monitoring dispersion with estimated process variance were derived and compared with the same chart but with assumed known process parameters.

TL;DR: In this article, the authors introduce a specific class of product kernels whose order is suitably defined in such a way to obtain L 2 risk formulas whose structure can be compared to their Euclidean counterparts.

TL;DR: In this article, it was shown that when the number of experiments is finite, the optimal design of multiresponse experiments can be computed by second-order cone programming (SOCP).

TL;DR: A spline-backfitted kernel smoothing method is proposed for partially linear additive model that is oracally efficient and fast to compute and application to the Boston housing data serves as a practical illustration of the method.

TL;DR: In this paper, a group bridge estimator is proposed to select grouped variables and study their asymptotic properties when the number of covariates increases along with the sample size.

TL;DR: In this paper, the power of the transformation is estimated for a class of power-transformed threshold GARCH models and the asymptotic properties of the quasi-maximum likelihood estimator (QMLE) are established under mild conditions.

TL;DR: This paper proposes a method based on a biorthogonal wavelet thresholding rule that is adaptive with respect to the nature of the support and the regularity of the signal, but that is also robust in practice to this curse of support.

TL;DR: In this article, a randomized design that assigns the MTD with probability that approaches one as the size of the experiment goes to infinity and estimates the maximum tolerated dose (MTD) consistently was proposed.

TL;DR: This work introduces a family of mixtures of modified t-factor analyzers that uses this generalized version of the factor analysis covariance structure, and applies the recently published Gaussian analogue to this family under the model-based classification and discriminant analysis paradigms for the first time.

TL;DR: In this paper, the identifiability of parameters for a broad class of random graph mixture models has been investigated, which are characterized by a partition of the set of graph nodes into latent (unobservable) groups and connectivities between nodes are independent random variables when conditioned on the groups of the nodes being connected.

TL;DR: In this article, a nonparametric test for the assumption of perfect ranking was proposed, which corresponded to the Jonckheere-Terpstra-type test statistic.

TL;DR: The aim of this paper is to study both the pointwise and uniform consistencies of the kernel regression estimate and to derive also rates of convergence whenever functional stationary ergodic data are considered and to extend the dependence setting to cases that are not covered by the usual mixing structures.

TL;DR: In this article, a three-parameter distribution which is called beta-negative binomial (BNB) distribution, a beta mixture of negative binomial distribution, is derived, and closed form and factorial moment of the BNB distribution are derived.

TL;DR: In this paper, the authors proposed the likelihood function for symbolic data and illustrate its applications by finding the maximum likelihood estimators for the mean and the variance of three common types of symbolic-valued random variables: interval-valued, histogram-valued and triangular distribution-valued variables.

TL;DR: In this paper, the maximum likelihood estimators (MLEs) of the Weibull parameters were derived and the asymptotic distributions of the MLE estimators were used to construct approximate confidence intervals.

TL;DR: In this paper, three different mixture models based on the Birnbaum-Saunders (BS) distribution, viz., mixture of two different BS distributions, mixture of a BS distribution and a length-biased version of another BS distribution, and mixture of the two distributions and its lengthbiased version, were considered.

TL;DR: The authors developed two empirical likelihood-based inference procedures for longitudinal data under the framework of quantile regression, which avoid estimating the unknown error density function and the intra-subject correlation involved in the asymptotic covariance matrix of the quantile estimators.

TL;DR: In this paper, the existence and consistency of the Maximum Likelihood estimator of the parameters of heterogeneous mixtures of Gaussian and uniform distributions with known number of components are shown under constraints to prevent the likelihood from degeneration and to ensure identifiability.

TL;DR: In this article, the EM algorithm is used to estimate the parameters of the lognormal model based on left truncated and right censored data, and the maximization step of the algorithm is carried out by two alternative methods, with one involving approximation using Taylor series expansion (leading to approximate maximum likelihood estimate) and the other based on the EM gradient algorithm ( Lange, 1995 ).

TL;DR: In this paper, the authors proposed an alternative approach in order to obtain pointwise confidence intervals by means of a bootstrap procedure, for which they have obtained its asymptotic validity.

TL;DR: In this article, the authors consider portmanteau tests for testing the adequacy of structural vector autoregressive moving-average (VARMA) models under the assumption that the errors are uncorrelated but not necessarily independent.

TL;DR: In this article, simple approximate prediction intervals based on the joint distribution of the past samples and the future sample are proposed for the binomial and Poisson distributions are reviewed and compared.

TL;DR: In this article, a new three-parameter ageing distribution called the Weibull-Poisson (WP) distribution was proposed, which generalizes the exponential-poisson (EP) distribution introduced by Kus (2007) and has a more general form of failure rate (hazard rate) function.

TL;DR: A modified Laplace approximation is derived when the number of random effects is increasing at a lower rate than the sample size and an approximate likelihood method based on the asymptotic expansion of the log-likelihood is proposed which is maximized using a quasi-Newton algorithm.

TL;DR: In this article, a progressive type-II censored sample from the generalized Rayleigh distribution was used to estimate the model parameters and predict the unobserved removed data, and the Gibbs and Metropolis samplers were used to predict the life lengths of the removed units in multiple stages of the progressively censored sample.

TL;DR: In this article, the authors propose to include Weibull tail-distributions in a more general family of distributions, which includes the whole Frechet maximum domain of attraction as well as log-Weibull-distribution.