Displaying 8 results from an estimated 8 matches for "estmat".
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estat
2008 Nov 27
2
Regression Problem for loop
Dear all,
I have wrote a code for a linear regression. I want to
write a loop for so, that I can get estimate for pavlues for six predictors.
But I am getting for estmate for only last one. How can I get pvalues for
all my predictors in a loop??
Anticipating your help
Thanks
Ales
> mat<-matrix(rnorm(36),nrow=6)
> mat
[,1] [,2] [,3] [,4]
[,5] [,6]
[1,] 1.10536338 -0.7613770 -1.7100569 -1....
2012 May 10
2
Outcome~predictor model evaluation, repeated measurements
...ping variable.
I would like know the correlation of Y with X (Y~X) and the effect of
within subject variance on this correlation. And thus, overall significance
and correlation.
Will it be valid to fit lm to all combinations of x and y and take an
average values of p and R-squared?
Usually, I estmate the correlation using simple lm between outcome and
averaged predictor (1-to-1, i.e. 20 outcomes versus 20 predictors).
However, I would like to take in account variations associated with
replicated measurements (i.e. the same 20 outcomes versus 20 predictors
replicated say 3 times), and, therefor...
2012 Feb 01
3
Probit regression with limited parameter space
...produce the hessian matrix, I
used hessian (numDeriv) to calculate it. However, the standard errors
calculated using hessian function are quite different from the ones
generated by the glm function, although the parameter estimates are very
close. I was wondering what makes this difference in the estmation of
standard errors and how this computation is carried out in glm.
2) Does any one know how to estimate a constrained probit model in R (to be
specific, I need to restrain the range of three parameters to [-1,1])?
Among the optimation functions, so far nlminb and spg work for my problem,
but n...
2007 Mar 15
0
Seemingly Unrelated Regressions question - not R question
Does anyone know where I can find a proof of the fact that when each X
matrix in a SUR is the same,
then SUR estimation is equivalent to OLS estmation. The proof is
supposedly in William Greene's book but that book
costs 157.00 an has mixed reviews so I am reluctant to purchase it.
Thanks.
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This is not an offer (or solicitation of an offer) to buy/se...{{dropped}}
2008 Oct 28
1
help on package or code for simutaneous equation probit(logit) model
Dear List
I am trying to fit a simutaneous equation logit model. i.e., the
response variables of the structured equations are binomial, I am not
sure if systemfit can do this job. A google search doesn't yield too
much helpful information. Your knowledge on any other packages or
codes are appreciated.
Thanks
will
2005 Jan 18
1
lme confusion
Hi, this is my first time using the nlme package, and I ran into the
following puzzling problem.
I estimated a mixed effects model using lme, once using groupedData, once
explicitly stating the equations. I had the following outputs. All the
coefficients were similar, but they're always slightly different, making me
think that it's not due to numerical error.
Also, what is the
2003 Jun 25
2
within group variance of the coeficients in LME
Dear listers,
I can't find the variance or se of the coefficients in a multilevel model
using lme.
I want to calculate a Chi square test statistics for the variability of the
coefficients across levels. I have a simple 2-level problem, where I want to
check weather a certain covariate varies across level 2 units. Pinheiro
Bates suggest just looking at the intervals or doing a rather
2002 Apr 22
3
glm() function not finding the maximum
Hello,
I have found a problem with using the glm function with a gamma
family.
I have a vector of data, assumed to be generated by a gamma distribution.
The parameters of this gamma distribution are estimated in two ways (i)
using the glm() function, (ii) "by hand", using the optim() function.
I find that the -2*likelihood at the maximum found by (i) is substantially
larger than that