Displaying 7 results from an estimated 7 matches for "cofficient".
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coefficient
2011 Jun 07
3
Logistic Regression
...s
that are categorical in nature and the depndent variable is dichotomus.
Initially I run univariate analysis and added the variables with significant
p-values (p<0.25) in my full model.
I have three confusions. Firstly, I am looking for confounding variables by
using formula "(crude beta-cofficient - adjusted beta-cofficient)/ crude
beta-cofficient x 100" as per rule if the percentage of any variable is >10%
than I have considered that as confounder. I wanted to know that from
initial model i have deducted one variable with insignificant p-value to
form adjusted model. Now how will i...
2012 Apr 10
2
lm()
People, help me please!
How to use lm() function to defind a cofficient for 7-polinom, and what
expression should I put in /formula/
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2011 Apr 16
3
lme4 problem: model defining and effect estimation ------ question from new bird to R community from SAS community
...intercept 2 | sire 2 0
dam(sire) 1 1 0 0 0 0 0 0 0 0 / divisor=2;
estimate 'sire 1 BLUP with dam 1'
intercept 1 | sire 1 0
dam(sire) 1 0;
ods select CovParms Estimates;
run;
# Estimate statement define predictable functions. All fixed effect
cofficient must appear first and then random effect coefficients. The fixed
and random
#effect cofficient are seperated by |
****************Expected outputs according to SAS
*************************************
Estimate
sire 1 BLUP "broad 2.2037
sire 1 BLUP "narrow"...
2004 Mar 05
1
Constraining coefficients
Hello All:
I have a binomial model with one covariate, x1, treated as a factor with
3 levels. The other covariate is measured x2 <- 1:30. The response, y,
is the proportion of successes out of 20 trials.
glm(cbind(y, 20 - y) ~ x1 * x2, family = binomial)
Now, I would like to constrain the cofficients on 2 levels of the
factor, x1, to be identical and test the difference between these models
by a likelihood ratio test.
How can I get glm() to constrain the coefficients on 2 levels to be the
same?
Thanks,
ANDREW
2003 Apr 21
2
piece wise functions
...#39;*f_1(x)+ ... + A_p'*f_p(x) with x >= C
Functions f_1, f_2, ... f_p are known.
Is there anything in R for that?
I have tried to use nonlinear (nls package)
regression, "forcing" with the "nls" function the shape of the surface,
but it does not work.
By the way, the cofficients A_i have to be positive, but I suppose this is
another question.
Thanks
Casiano
casiano at ull.es
2010 Sep 02
1
Help on glm and optim
...(5,10,15,20,30,40,60,80,100),
lot1 = c(118,58,42,35,27,25,21,19,18),
lot2 = c(69,35,26,21,18,16,13,12,12))
fit1 <- glm(lot1 ~ log(u), data=clotting, family=Gamma)
# Step 2: use optim
# define loglikelihood function to be maximized over
# theta is a vector of three parameters: intercept, cofficient for log(u) and dispersion parameter
loglik <- function(theta,data){
E <- 1/(theta[1]+theta[2]*log(data$u))
V <- theta[3]*E^2
loglik <- sum(dgamma(data$lot1,shape=1/theta[3],rate=1/(E*theta[3]),log=T))
return(loglik)
}
# use the glm result as initial valu...
2008 Jan 18
0
forming a linear discriminant function from the output of lda()
...da(Region ~ Mo + Ba, data = wine, prior = c(1, 1)/2)
Prior probabilities of groups:
2 3
0.5 0.5
Group means:
Mo Ba
2 0.1461111 0.2810000
3 0.1479167 0.1079167
Coefficients of linear discriminants:
LD1
Mo -5.636024
Ba -22.069187
I am having trouble going from the cofficients derived from the
spherical within group covariance to the
function I am able to obtain in the other programs.
The rest of the problem set up for all programs are: Region = group
assignment, prior = equal priors and
I do not do any data pretreatment prior to analysis.
Any help would be great.
T...