On Dec 10, 2011, at 11:48 AM, tony333 wrote:
X8 = c(0.42808332, 0.14058333, 0.30558333, 0.09558333, 0.01808333,
-0.09191666, -0.11441666, -0.12941666, 0.13808333, -0.31691666,
0.25308333
,-0.20941666 ,0.02808333, -0.04441667, -0.43691666)
xy.lm = lm(Y~X8)
z = predict(xy.lm,list(X8=X
X8 = c(0.42808332, 0.14058333, 0.30558333, 0.09558333, 0.01808333,
-0.09191666, -0.11441666, -0.12941666, 0.13808333, -0.31691666, 0.25308333
,-0.20941666 ,0.02808333, -0.04441667, -0.43691666)
xy.lm = lm(Y~X8)
z = predict(xy.lm,list(X8=X8))
sz = coef(xy.lm)[1]+(coef(xy.lm)[2])*X8
is th
X8 = c(0.42808332, 0.14058333, 0.30558333, 0.09558333, 0.01808333,
-0.09191666, -0.11441666, -0.12941666, 0.13808333, -0.31691666, 0.25308333
,-0.20941666 ,0.02808333, -0.04441667, -0.43691666)
Y =c(370.6 , 887.6 ,3610.88333 , 435.1 , 1261.38333 ,
-741.11667,-3231.36667 ,-
Hi
Did you find any difference? The results shall be same (with only rounding
error). Can you show us some example where you get substantial difference?
Regards
Petr
>
> i do not know what is the difference between predict() and coef()
> i use the two function give me different result
> zz =
i do not know what is the difference between predict() and coef()
i use the two function give me different result
zz = predict(xy.lm,list(T8=T8))
ss = coef(xy.lm)[1]+(coef(xy.lm)[2])*T8
where is t8 is the data used in prediction did not use in the fitting in
training sample where every sample is 1
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