# 비선형 회귀

비선형 고정효과 및 혼합효과 회귀 모델

비선형 회귀 모델에서는 응답 변수를 모델 계수와 예측 변수의 선형 결합으로 표현할 필요가 없습니다. `NonLinearModel` 객체를 사용하거나 사용하지 않고 비선형 회귀를 수행할 수 있습니다. 또는 대화형 방식의 툴 `nlintool`을 사용하여 수행할 수도 있습니다.

## 함수

모두 확장

 `fitnlm` 비선형 회귀 모델 피팅 `feval` Evaluate nonlinear regression model prediction `predict` Predict response of nonlinear regression model `random` Simulate responses for nonlinear regression model `partialDependence` Compute partial dependence (R2020b 이후) `plotPartialDependence` Create partial dependence plot (PDP) and individual conditional expectation (ICE) plots `plotResiduals` Plot residuals of nonlinear regression model
 `nlinfit` 비선형 회귀 `nlintool` Interactive nonlinear regression `nlparci` 비선형 회귀 모수 신뢰구간 `nlpredci` Nonlinear regression prediction confidence intervals
 `nlmefit` Nonlinear mixed-effects estimation `nlmefitsa` Fit nonlinear mixed-effects model with stochastic EM algorithm
 `dummyvar` Create dummy variables `hougen` Hougen-Watson 모델 `statset` Create statistics options structure `statget` Access values in statistics options structure

## 객체

 `NonLinearModel` Nonlinear regression model

## 도움말 항목

### 혼합효과

• 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 the `stats` structure, which is returned by both `nlmefit` and `nlmefitsa`, to determine the quality of your model.