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前言自从高斯发明最小二乘法以来,它的历史已有一百余年。迄今,当求算观測值之最或然值时,高斯約化法仍广泛应用在各个生产部門中。因此,有关的高等院校在讲授这门課程时,必須介紹此法。但高斯約化法所形成的規律,按古典的方法推导非常复杂。本文借助于矩陣代数这一工具,应用概率論的原理,詳細地討論了此法。使得推导过程非常簡单。我們不准备介紹很多矩陣代数的理論,只局限在閱讀本文所必須的那些結果。一、矩陣的微分理論及其他
Foreword Since Goss invented the least square method, its history has been more than one hundred years. To date, Gaussian reduction is still widely used in various production sectors when calculating the most probable value of observations. Therefore, the relevant colleges and universities must introduce this method when teaching this course. However, the laws formed by the Gaussian reduction method are very complicated to deduce according to classical methods. This paper discusses this method in detail by using the tool of matrix algebra and applying the principle of probability theory. Make the derivation process very simple. We are not ready to introduce many theories of matrix algebra, but only those results that are necessary to read this article. First, the differential theory of matrix and other