非线性回归
非线性固定效应回归模型和非线性混合效应回归模型
在非线性回归模型中,响应变量不需要表示为模型系数和预测变量的线性组合。您可以使用或不使用 NonLinearModel
对象来执行非线性回归,也可以使用交互式工具 nlintool
来执行非线性回归。
函数
对象
NonLinearModel | Nonlinear regression model |
主题
非线性模型
- Nonlinear Regression
Parametric nonlinear models represent the relationship between a continuous response variable and one or more continuous predictor variables. - Nonlinear Regression Workflow
Import data, fit a nonlinear regression, test its quality, modify it to improve the quality, and make predictions based on the model. - 加权非线性回归
此示例说明如何将非线性回归模型与具有非常量误差方差的数据进行拟合。 - Pitfalls in Fitting Nonlinear Models by Transforming to Linearity
This example shows pitfalls that can occur when fitting a nonlinear model by transforming to linearity. - Nonlinear Logistic Regression
This example shows two ways of fitting a nonlinear logistic regression model.
混合效应
- Mixed-Effects Models
Mixed-effects models account for both fixed effects (which represent population parameters, assumed to be the same each time data is collected) and random effects (which act like additional error terms). - Mixed-Effects Models Using nlmefit and nlmefitsa
Fit a mixed-effects model, plot predictions and residuals, and interpret the results. - Examining Residuals for Model Verification
Examine thestats
structure, which is returned by bothnlmefit
andnlmefitsa
, to determine the quality of your model.