dear R users,
I have fit the lm() on a mtrix of responses.
i.e M1 = lm(cbind(R1,R2)~ X+Y+0). When i use
summary(M1), it shows details for R1 and R2
separately. Now i want to use stepAIC on these models.
But when i use stepAIC(M1) an error message comes
saying that dropterm.mlm is not
Dear All,
1)Can I use lm() to fit more than one response in
single expression. e.g data is a matrix of these
variables
R1 R2 R3 X Y Z
1 2 1 1 2 3
Now i wnat to fit R1:R3 ~ X+Y+Z.
2) How can i use Singular Value decomposition (SVD) as
an alternate to lsq.
Regards,
Hi all,
I am trying to fit full quadratic model i.e liear +
square + interaction terms to my data (216 data
points), so in my case coefficients are 28 (6
parameters). When i look into summary lm() of model
all cross terms coefficients are NA. What does this
mean? Is the regression is not able to
Dera R users,
I have written a function which computes variance, sd,
r^2, R^2adj etc. But i am not able to return all of
them in return statement.
So how to return more than one variable from
function. In C i used to return by pointers etc. is
there any way like that.
Thanks in advance.
Hello
I want to know that in R which library/package
supports Design of Experiments(I,D etc optimality or
conventional DOE)
Regards,
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I am trying to use lm() for resression followed by
stepAIC function. Now when i try to use to predict for
some input, predict() gives a warning : prediction
from a Rank deficient matrix may be misleading.
As I am new to R (or to statistics) How alarming this
warning may be?
Regards,
I am interested in Neural network models in R. Is
there any reference material/tutorial which i can use.
Regards,
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I want to plot variation of more than one variable in
single plot with different point types and points
sizes . Can someone help me to do that,
Thanks in advance.
vinod
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I am trying to fit a model with 4 parameteres on
one response. I have 32 points and the model contains
linear, quadratic and interaction terms. Now when i
apply the Step AIC method most of my square terms drop
out (which i think is not correct if physics is
concerned) So is there any way to