x****h 发帖数: 78 | 1 Simple linear regression S1: Y~x(1) (i.e., Y=a1*x(1)+a0); R2 (coefficient of
determination) = 0.01 ;
Simple linear regression S2: Y~x(2) (i.e., Y=b1*x(2)+b0); R2 (coefficient of
determination) = 0.02 ;
Then multiple regression M3:Y~x(1) and x(2)(i.e., Y=c2*x(2)+c1*x(1)+c0); wha
t is the min and max of the R2 for this regression?
thanks! | B******5 发帖数: 4676 | | t**c 发帖数: 539 | 3 agree
【在 B******5 的大作中提到】![](/moin_static193/solenoid/img/up.png) : 0.02 0.03?
| x****h 发帖数: 78 | 4 Can you share some details on how you arrive at this conclusion? thanks.
【在 t**c 的大作中提到】![](/moin_static193/solenoid/img/up.png) : agree
| c*********r 发帖数: 1802 | 5 for same Y, SSTO 不变。
in S1, R2= SS(x1)/SSTO=0.01;
in S2, R2= SS(x2)/SSTO=0.02;
in M3, R2= [SS(x2)+SS(x1|x2)]/SSTO
if x1, x2 independent, SS(x1)=SS(x1|x2), then R2=0.03
if x1, x2 linear, SS(x1|x2)=0, then R2=0.02.
My understanding。。。 | a****g 发帖数: 8131 | 6 there is a kind of factors, I forgot its name, seems likely repressive
factors or whatever
I think the up-limit of r2 is 1 |
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