www.gusucode.com > stats 源码程序 matlab案例代码 > stats/SpecifyModelUsingFormulaandSpecifyVariablesExample.m
%% Stepwise Regression Using Specified Model Formula and Variables % Perform stepwise regression using variables stored in a dataset array. % Specify the starting model using Wilkinson notation, and identify the % response and predictor variables using optional arguments. %% % Load the sample data. load hospital %% % The hospital dataset array includes the gender, age, weight, and smoking % status of patients. %% % Fit a linear model with a starting model of a constant term and |Smoker| % as the predictor variable. Specify the response variable, |Weight|, and % categorical predictor variables, |Sex|, |Age|, and |Smoker|. mdl = stepwiselm(hospital,'Weight~1+Smoker',... 'ResponseVar','Weight','PredictorVars',{'Sex','Age','Smoker'},... 'CategoricalVar',{'Sex','Smoker'}) %% % At each step, |stepwiselm| searches for terms to add and remove. At first % step, stepwise algorithm adds |Sex| to the model with a $p$-value of 6.26e-48. % Then, removes Smoker from the model, since given |Sex| in the model, the % variable |Smoker| becomes redundant. |stepwiselm| only includes |Sex| % in the final linear model. The weight of the patients do not seem to differ % significantly according to age or the status of smoking.