如果您只想使用部分数据进行回归,您可以自己过滤掉proc reg它:
proc reg data=mydata (where=(X1 Between Q1 and Q3 and X2 > 100))
PLOTS(ONLY)=(DIAGNOSTICS FITPLOT RESIDUALS);
model Y = X1 X2 X3;
即 ifQ1和Q3are 中的字段myData。如果没有,您可以为它们创建宏变量。例如
%let Q1 = 50;
%let Q3 = 250;
proc reg data=mydata (where=(X1 Between &Q1. and &Q3. and X2 > 100))
PLOTS(ONLY)=(DIAGNOSTICS FITPLOT RESIDUALS);
model Y = X1 X2 X3;
这是如果您预先知道 Q1 和 Q3。
如果Q1andQ3是另一个数据集中的字段,proc sqlwithselect Q1, Q3. into :Q1, :Q3或 data step withcall symput('Q1', Q1); call symput('Q3', Q3);可以完成这项工作。
阅读您的评论后进行编辑,解释Q1等是分位数:
以下示例可能包含您需要的所有构建块
ods graphics on;
proc means data=SASHELP.CLASS noprint;
var Height Weight;
output out=CLASS_Q
P25(Height Weight)=Height_Q1 Weight_Q1
P75(Height Weight)=Height_Q3 Weight_Q3;
run;
data _NULL_;
set CLASS_Q;
call symput('Height_Q1', Height_Q1);
call symput('Height_Q3', Height_Q3);
call symput('Weight_Q1', Weight_Q1);
call symput('Weight_Q3', Weight_Q3);
run;
%put _user_; *just to debug;
proc reg data=SASHELP.CLASS
(where=(Height Between &Height_Q1. and &Height_Q3. and Weight > &Weight_Q1.))
PLOTS(ONLY)=(DIAGNOSTICS FITPLOT RESIDUALS);
model Age = Height Weight;
run;