Analysis of punitive damages in the context of economic law based on the singular value analysis method

Abstract

Based on some problems in the punitive damages system that are not conducive to economic development, we take the perspective of economic law to play a positive role in promoting the further improvement of punitive damages. In this paper, the rank of punitive damages is first defined by the singular value analysis algorithm, and the function is set up as a diagonal matrix composed of different vectors, and the square root of the decomposition eigenvalue is the singular value of the matrix. Then the matrix nodes are calculated, and each node is divided into two column blocks and predicted, and the number of nodes is input for the eigenvalue decomposition. The matrix regression coefficients of the independent variables are examined after the decomposition is performed, and the fit of the singular value analysis algorithm in dealing with the compensation problem is derived from this coefficient. The experimental results from a region of the United States show that among 100 large punitive damages cases exceeding $100 million between January 2009 and December 2018, the number of cases of punitive damages in 2010, 2011, and 2013 was only one, and the highest number reached 12 in 2018 illustrating the accuracy of singular value analysis in locating punitive damages, which helps to promote the construction and development of the punitive compensation system and contribute to the stable development of the social economy.

Keywords

• singular value analysis algorithm
• penalized compensation
• heterovector
• eigenvalue decomposition
• diagonal matrix
• 68t99