摘要
对非线性回归模型进行非线性最小二乘估计一般需要确定参数初始值.在非线性回归模型中,General Logistic模型和Von Bertalanffy模型是二个含有四参数的增长曲线模型,对数据的拟合有较强的适应性,应用较为广泛.本文给出这两个模型参数初始值的确定方法,并应用于实际拟合,得到很好的效果.
The non-linearized least square estimate commonly need to confirms parameters initial values about non-linearized regress model. In non-linearized regress model, General Logistic model and Von Bertalanffy model are two 4 parameters increase curve model, they have strong adaptability about data fitting and rather abroad application. This paper givesThe determine method of parameters initial values of two model and applies to practice fitting, find good effect.
出处
《数学的实践与认识》
CSCD
北大核心
2009年第9期109-114,共6页
Mathematics in Practice and Theory
关键词
模型
非线性最小二乘估计
初始值
拟合
model
non-linearized least square estimate
initial values
fitting
