hi,
I considered multivariate multiple regression for respons, predictor, each 5
dimension.
on going process, through
initb <- eigen(temp)$vectors[,1:3]
temp <- vhalf%*%Kproduct(Ir,initb)
(herein 'vhalf' is root for inverse of covariance matrix
and 'Kproduct' is Kronecker product)
and then process regression. However,
I have tried using the 'lm' function and i get the result, like this.
( 'xi'
is 25 by 1 vector )
> reg <- lm(xi~temp)
>
> reg
Call:
lm(formula = xi ~ temp)
Coefficients:
(Intercept) temp1 temp2 temp3 temp4
temp5 temp6 temp7
-3.704e-15 2.434e-02 4.087e-02 NA -5.241e-01
-1.213e-02 NA -1.960e-02
temp8 temp9 temp10 temp11 temp12
temp13 temp14 temp15
6.516e-03 NA -6.651e-02 8.865e-02 NA
4.272e-02 -3.085e-02 NA
Coefficients for multiple of three are 'NA'.
I'd like get any value, so i directly tried to calculate using matrix.
That result,
> ginv(t(temp)%*%temp)%*%t(temp)%*%xi
[,1]
[1,] 0.0239396255
[2,] 0.0402622882
[3,] -0.0058317229
[4,] -0.5216032391
[5,] -0.0083355651
[6,] 0.0362961561
[7,] -0.0195581411
[8,] 0.0065824700
[9,] 0.0006407087
[10,] -0.0668295201
[11,] 0.0881623108
[12,] -0.0046706822
[13,] 0.0427419205
[14,] -0.0308143260
[15,] 0.0003160107
why don't I get coefficient value using the 'lm' function?
and what's different to two way?
I really need your help.
I waiting your answer !
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References
1. mailto:sluvsek at hanmail.net