Publication

MATHICSE Technical Report : An algorithm for computing minimal Geršgorin sets

2015
Working Papers

Abstract

The first algorithms for computing the minimal Geršgorn set were developed by Varga et all. in [17] for the use on small and medium size (dense) matrices. Here, we first discuss the existing methods and present a new approach based on the modified Newton’s method to find zeros of the parameter dependent left-most eigenvalue of a Z-matrix. Additionally, sampling technique used in the original work is replaced by a special curve tracing procedure. The advantages of the new approach are presented on several test examples that arise in practical applications.

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2015
Working Papers

Abstract

Official source

Related concepts (29)

Sampling (statistics)

In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population, and thus, it can provide insights in cases where it is infeasible to measure an entire population.

Grid computing

Grid computing is the use of widely distributed computer resources to reach a common goal. A computing grid can be thought of as a distributed system with non-interactive workloads that involve many files. Grid computing is distinguished from conventional high-performance computing systems such as cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed (thus not physically coupled) than cluster computers.

Convenience sampling

Convenience sampling (also known as grab sampling, accidental sampling, or opportunity sampling) is a type of non-probability sampling that involves the sample being drawn from that part of the population that is close to hand. This type of sampling is most useful for pilot testing. Convenience sampling is not often recommended for research due to the possibility of sampling error and lack of representation of the population. But it can be handy depending on the situation. In some situations, convenience sampling is the only possible option.

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