Appendix to chapter 2

Eric A. Monke, Francisco Avillez, Scott R. Pearson, Gaetano Marenco, Carlo Perone-Pacifico
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Abstract

Appendix to Chapter 2 This appendix has two purposes. One is to reformulate the exemplar model using matrix algebra. This is important for speeding up the computational process, shortening the length of the code, and simplifying the program. Furthermore, matrix operators are quite useful for other topics covered in this book. The second purpose is to describe the computer program that was used to qualitatively analyze the predictions of the exemplar model (i.e., the program used to compute Figure 6.) Review of Matrix Algebra. Matrix algebra is a mathematical formalism that based on objects called column vectors, row vectors, and matrices; as well as matrix operators such as transpose, matrix sum, scalar multiplication, inner product, matrix product, and Kronecker product, and matrix inverse. For our purposes, an n by m matrix is just a table of values that has n rows and m columns, and the entire table is denoted by a bold face letter such as X. An example of a 2 (row) by 3 (column) matrix is shown below.
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第二章附录
本附录有两个目的。一种是用矩阵代数重新表述范例模型。这对于加快计算过程、缩短代码长度和简化程序非常重要。此外,矩阵算子对于本书所涉及的其他主题也非常有用。第二个目的是描述用于定性分析范例模型预测的计算机程序(即用于计算图6的程序)。矩阵代数复习。矩阵代数是一种基于列向量、行向量和矩阵的数学形式;以及矩阵运算符,如转置,矩阵和,标量乘法,内积,矩阵乘积,和克罗内克积,和矩阵逆。出于我们的目的,一个n × m矩阵只是一个包含n行和m列的值的表,整个表用一个粗体字母表示,比如x。下面显示了一个2(行)× 3(列)矩阵的例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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