On conditional variance estimation in nonparametric regressionStatistics and Computing - Tập 23 - Trang 261-270 - 2012
Siddhartha Chib, Edward Greenberg
In this paper we consider a nonparametric regression model in which the
conditional variance function is assumed to vary smoothly with the predictor. We
offer an easily implemented and fully Bayesian approach that involves the Markov
chain Monte Carlo sampling of standard distributions. This method is based on a
technique utilized by Kim, Shephard, and Chib (in Rev. Econ. Stud. 65:361–393,
1998) f... hiện toàn bộ
Optimal designs for dose-escalation trials and individual allocations in cohortsStatistics and Computing - Tập 32 - Trang 1-16 - 2022
Belmiro P. M. Duarte, Anthony C. Atkinson, Nuno M. C. Oliveira
Dose escalation trials are crucial in the development of new pharmaceutical
products to optimize the amount of drug administered while avoiding undesirable
side effects. We adopt the framework established by Bailey (Stat Med
28(30):3721–3738, 2009. https://doi.org/10.1002/sim.3646 ) where the individuals
are grouped into cohorts, to the subjects in which the placebo or previously
defined doses are... hiện toàn bộ
A new method for the estimation of variance matrix with prescribed zeros in nonlinear mixed effects modelsStatistics and Computing - Tập 19 - Trang 129-138 - 2008
Djalil Chafaï, Didier Concordet
We propose a new method for the Maximum Likelihood Estimator (MLE) of nonlinear
mixed effects models when the variance matrix of Gaussian random effects has a
prescribed pattern of zeros (PPZ). The method consists of coupling the recently
developed Iterative Conditional Fitting (ICF) algorithm with the Expectation
Maximization (EM) algorithm. It provides positive definite estimates for any
sample ... hiện toàn bộ
New mixed portmanteau tests for time series modelsStatistics and Computing - Tập 34 - Trang 1-15 - 2024
Esam Mahdi
This article proposes omnibus portmanteau tests for contrasting adequacy of time
series models. The test statistics are based on combining the autocorrelation
function of the conditional residuals, the autocorrelation function of the
conditional squared residuals, and the cross-correlation function between these
residuals and their squares. The maximum likelihood estimator is used to derive
the as... hiện toàn bộ
Distributed adaptive nearest neighbor classifier: algorithm and theoryStatistics and Computing - Tập 33 - Trang 1-23 - 2023
Ruiqi Liu, Ganggang Xu, Zuofeng Shang
When data is of an extraordinarily large size or physically stored in different
locations, the distributed nearest neighbor (NN) classifier is an attractive
tool for classification. We propose a novel distributed adaptive NN classifier
for which the number of nearest neighbors is a tuning parameter stochastically
chosen by a data-driven criterion. An early stopping rule is proposed when
searching ... hiện toàn bộ
Embedded topics in the stochastic block modelStatistics and Computing - Tập 33 - Trang 1-20 - 2023
Rémi Boutin, Charles Bouveyron, Pierre Latouche
Communication networks such as emails or social networks are now ubiquitous and
their analysis has become a strategic field. In many applications, the goal is
to automatically extract relevant information by looking at the nodes and their
connections. Unfortunately, most of the existing methods focus on analysing the
presence or absence of edges and textual data is often discarded. However, all
co... hiện toàn bộ
Switched diffusion processes for non-convex optimization and saddle points searchStatistics and Computing - Tập 33 - Trang 1-16 - 2023
Lucas Journel, Pierre Monmarché
We introduce and investigate stochastic processes designed to find local
minimizers and saddle points of non-convex functions, exploring the landscape
more efficiently than the standard noisy gradient descent. The processes switch
between two behaviours, a noisy gradient descent and a noisy saddle point
search. It is proven to be well-defined and to converge to a stationary
distribution in the lon... hiện toàn bộ
Estimation of 2D jump location curve and 3D jump location surface in nonparametric regressionStatistics and Computing - Tập 22 - Trang 17-31 - 2010
Chih-Kang Chu, Jhao-Siang Siao, Lih-Chung Wang, Wen-Shuenn Deng
A new procedure is proposed to estimate the jump location curve and surface in
the two-dimensional (2D) and three-dimensional (3D) nonparametric jump
regression models, respectively. In each of the 2D and 3D cases, our estimation
procedure is motivated by the fact that, under some regularity conditions, the
ridge location of the rotational difference kernel estimate (RDKE; Qiu in
Sankhyā Ser. A 59... hiện toàn bộ