摘要
将一元线性回归总体最小二乘平差模型展开后,以因变量和自变量改正数的平方和最小为约束条件,推导其总体最小二乘的迭代算法,并将模型扩展到多元线性回归,进一步得到线性回归模型的总体最小二乘算法。通过实例分析,证明算法的可行性和合理性。
With a linear regression of total least squares adjustment model launched,a total least squares iterative algorithm is derived from the constraint condition that the sum of squares of correction of dependent variable and independent variables is minimum.The model is extended to the multivariate linear regression,and further developed to the total least squares linear regression model algorithms.Through the example analysis,the results show that the algorithm is feasible and reasonable.
出处
《测绘工程》
CSCD
2015年第1期36-39,共4页
Engineering of Surveying and Mapping
关键词
总体最小二乘
线性回归模型
迭代算法
自变量
平差模型
total least squares
linear regression model
iteration algorithm
independent variable
adjustment model
