BACKGROUND The aim of the present study was to evaluate potential psychosocial factors that impact Chinese female breast cancer patients to select breast reconstruction (BR), and potential connection of psychosocial outcomes with their satisfaction with BR. METHODS A total of 264 female breast cancer patients with mastectomy were recruited from 2012 to 2014. All patients were informed with BR...

Bousquet-Mélou and Petkovšek investigated the generating functions of multivariate linear recurrences with constant coefficients. We will give a reinterpretation of their results by means of division theorems for formal power series, which clarifies the structural background and provides short, conceptual proofs. In addition, extending the division to the context of differential operators, the ...

We study the average case complexity of a linear multivariate problem (LMP) defined on functions of d variables. We consider two classes of information. The first Λ std consists of function values and the second Λ all of all continuous linear functionals. Tractability of LMP means that the average case complexity is O((1/ε) p) with p independent of d. We prove that tractability of an LMP in Λ s...

The traditional linear Granger test has been widely used to examine the linear causality among several time series in bivariate settings as well as multivariate settings. Hiemstra and Jones [19] develop a nonlinear Granger causality test in bivariate settings to investigate the nonlinear causality between stock prices and trading volume. This paper extends their work by developing a non-linear ...

Multivariate nonlinear mixed-effects models (MNLMM) have received increasing use due to their flexibility for analyzing multi-outcome longitudinal data following possibly nonlinear profiles. This paper presents and compares five different iterative algorithms for maximum likelihood estimation of the MNLMM. These algorithmic schemes include the penalized nonlinear least squares coupled to the mu...

Multivariate analysis of variance (MANOVA) extends the ideas and methods of univariate ANOVA in simple and straightforward ways. But the familiar graphical methods typically used for univariate ANOVA are inadequate for showing how measures in a multivariate response vary with each other, and how their means vary with explanatory factors. Similarly, the graphical methods commonly used in multipl...

Multivariate functional data are increasingly encountered in data analysis, while statistical models for such data are not well developed yet. Motivated by a case study where one aims to quantify the relationship between various longitudinally recorded behavior intensities for Drosophila flies, we propose a functional linear manifold model. This model reflects the functional dependency between ...

Two types of M-estimators of the parameters of the multi-variate linear model are considered. The first type corresponds to coordinatewise M-estimators; the second is an extension of Maronna's (1976) proposal for the multivariate location case. Under some general conditions on the error distribution, on the design matrix and on the score functions, the asymptotic distribution of the coordinatew...

Learning from data means a process of information extraction from finite size samples in order to estimate an unknown dependency. A series of problems can be modeled in terms of a system that computes according to an unknown rule a response (output) for each input. The paper provides a series of results concerning the learning from data a linear regressive model in a multivariate framework. The...