We consider median regression and, more generally, a possibly infinite collection of quantile regressions in high-dimensional sparse models. In these models, the number of regressors p is very large, possibly larger than the sample size n, but only at most s regressors have a nonzero impact on each conditional quantile of the response variable, where s grows more slowly than n. Since ordinary q...

BACKGROUND The use of qualitative research (QR) methods is recommended as good practice in discrete choice experiments (DCEs). This study investigated the use and reporting of QR to inform the design and/or interpretation of healthcare-related DCEs and explored the perceived usefulness of such methods. METHODS DCEs were identified from a systematic search of the MEDLINE database. Studies were...

Directed migration of neurons is critical in the normal and pathological development of the brain and central nervous system. In Caenorhabditis elegans, the bilateral Q neuroblasts, QR on the right and QL on the left, migrate anteriorly and posteriorly, respectively. Initial protrusion and migration of the Q neuroblasts is autonomously controlled by the transmembrane proteins UNC-40/DCC, PTP-3/...

In this paper, we present the QR Algorithm with Permutations that shows an improved convergence rate compared to the classical QR algorithm. We determine a bound for performance based on best instantaneous convergence, and develop low complexity methods for computing the permutation matrices at every iteration. We use simulations to verify the improvement, and to compare the performance of prop...

This paper proposes a simplified QR-based selection criterion for the efficient optimization of multiple-input multiple-output (MIMO) precoding in a limited feedback system. The proposed selection criterion is developed which determines the precoder yielding the maximum of minimum diagonal entries of the upper triangular matrix of the QR-decomposition on the MIMO channel. Performance evaluation...

The present work continues the study of the stability of the functional equations of the type f(pr, qs) + f(ps, qr) = f(p, q) f(r, s) namely (i) f(pr, qs)+f(ps, qr) = g(p, q) g(r, s), and (ii) f(pr, qs)+f(ps, qr) = g(p, q) h(r, s) for all p, q, r, s ∈ G, where G is an abelian group. These functional equations arise in the characterization of symmetrically compositive sumform distance measures.

Although qualitative researches (QR) are invaluable in understanding complex healthcare situations, the quantitative systematic reviews could not treat them. To improve quality of healthcare services, results of QR should be considered in healthcare decision-making processes. Several methods and theories for synthesizing evidences of QR have been developed. In order to activate the narrative re...

Although the variable selection and regularization procedures have been extensively considered in literature for quantile regression (QR) scenario via penalization, many such fail to deal with data aberrations design space, namely, high leverage points (X-space outliers) collinearity challenges simultaneously. Some referred as influential observations tend adversely alter eigenstructure of matr...

5 QR Decomposition 7 5.1 Householder Reflections and Givens Rotations . . . . . . . . . . . . . . . . . . . . . . . 8 5.2 Gram-Schmidt orthonormalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 5.3 QR Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 5.4 Least Square Fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....

This study focuses on the performance of two classical dense linear algebra algorithms, the LU and the QR factorizations, on multilevel hierarchical platforms. We first introduce a new model called Hierarchical Cluster Platform (HCP), encapsulating the characteristics of such platforms. The focus is set on reducing the communication requirements of studied algorithms at each level of the hierar...