This paper develops two new models and evaluates the impact of using different weight matrices on parameter estimates and inference in three distinct spatial specifications for discrete response. These specifications rely on a conventional, sparse, inverse-distance weight matrix for a spatial auto-regressive probit (SARP), a spatial autoregressive approach where the weight matrix

This article investigates discrete-time matrix-weighted consensus of multi-agent networks over undirected and connected graphs. We first present protocols for the agents in common symmetric matrix weights with possibly different update rates switching network topologies. A special type non-symmetric matrix-weights that can render several control scenarios such as ones scaled/rotated updates aff...

A matrix-weighted graph is an undirected with a k×k symmetric positive semidefinite matrix assigned to each edge. Such graphs admit natural generalizations of the Laplacian and adjacency matrices, leading generalized notion expansion. Extensions some theorems about expansion hold for graphs—in particular, analogue expander mixing lemma one half Cheeger-type inequality. These results lead defini...

Abstract Finite mixtures of regressions with fixed covariates are a commonly used model-based clustering methodology to deal regression data. However, they assume assignment independence, i.e., the allocation data points clusters is made independently distribution covariates. To take into account latter aspect, finite random covariates, also known as cluster-weighted models (CWMs), have been pr...

The Wiener matrix and the hyper-Wiener number of a tree (acyclic structure), higher Wiener numbers of a tree that can be represented by a Wiener number sequence W, W,W.... whereW = W is the Wiener index, and R W k K    ,.... 2 , 1 is the hyper-Wiener number. The concepts of the Wiener vector and hyper-Wiener vector of a graph are introduced for the molecular graph of bi-phenylene. Moreover, ...

Since the existing floating car map-matching algorithms lead to high error rate when GPS data sampling rate is low, we propose a global-voting map matching algorithm. Based on floating car GPS track data, the algorithm do not only consider the influence to matching process caused by the topological information of road network but also the different spatial distance of GPS track data. In this ma...

The U-matrix has become a standard visualization of self-organizing feature maps (SOM). Here we present the abstract U-matrix, which formalizes the structures on a U-matrix such that distance calculations between best-matching units w.r.t. the height structures of a U-matrix are precisely defined (U-cell distance). This enables the assessment of the topological correctness of the SOM and the im...

  Introduction: Ordered subset expectation maximization (OSEM), is an effective iterative method for SPECT image reconstruction. The aim of this study is the evaluation of the role of system matrix in OSEM image reconstruction method using four different physical beam radiation models with three detection configurations. Methods: SPECT was done with an arc of 180 deg...