Displaying 7 results from an estimated 7 matches for "bernouilli".
2005 Jul 15
2
glm(family=binomial(link=logit))
...trying to make glm() work to analyze a toy logit system.
I have a dataframe with x and y independent variables. I have
L=1+x-y (ie coefficients 1,1,-1)
then if I have a logit relation with L=log(p/(1-p)),
p=1/(1+exp(L)).
If I interpret "p" as the probability of success in a Bernouilli
trial, and I can observe the result (0 for "no", 1 for "yes")
how do I retrieve the coefficients c(1,1,-1)
from the data?
n <- 300
des <- data.frame(x=(1:n)/n,y=sample(n)/n) # experimental design
des <- cbind(des,L=1+des$x-des$y) # L=1+x-y
des <- cbind(...
2008 May 13
1
Likelihood between observed and predicted response
...aussian model (normal or
log-normal abundances).
I would like to evaluate these models not on their capability of
adjustment but on their capability of prediction by calculating the
(log)likelihood between predicted and observed values for each type of
model.
I found the following formula for Bernouilli model :
-2 log lik = -2 sum (y*log phat + (1-y)*log(1-phat) ), with "phat" is
the probaility (between 0 and 1) and "y" is the observed values (0 or 1).
1) Is anybody can tell me if this formula is statistically true?
2) Can someone tell me what is the formula of the likelihoo...
2010 Dec 15
4
Generacion de binomiales correlacionadas
Buenas tardes,
Estoy interesado en generar observaciones de una distribucion binomial
bivariada en la que hay _cierto_ grado de correlacion (denotemoslo rho).
Podria por favor alguien indicarme como hacerlo en R?
Este es el contexto. Supongamos que se tienen dos experimentos en los que la
variable respuesta _sigue_ una distribucion binomial, i.e., X_i
~Binomial(n_i, p_i), i=1,2 y que, por ahora,
2006 Mar 21
0
finite mixture model, using flexmix
Dear R-users,
I would like to use the package flexmix to fit latent classes to a
regression model. My data are repeated measurements of bernouilli
variables so I can use the binomial family link to the glm function. The
design is not balanced, meaning that for some individuals in my data set
I have 10 measurements or more, for others I only have 5 or even less.
My question is the following. Can flexmix handle this unbalancedness in
the datas...
2005 Nov 22
1
what does the it when there is a zero events in the Logistic Regression with glm?
Dear all,
I have a question about the glm. When the events of an observation is 0,
the logit function on it is Inf. I wonder how the glm solve it.
An example:
Treat Events Trials
A 0 50
B 7 50
C 10 50
D 15 50
E 17 50
Program:
treat <- factor(c("A", "B", "C", "D", "E"))
events <- c(0, 7, 10, 15,
2008 Sep 22
1
Likelihood between observed and predicted response
...abundances).
>
> I would like to evaluate these models not on their capability of
> adjustment but on their capability of prediction by calculating the
> (log)likelihood between predicted and observed values for each type of
> model.
>
> I found the following formula for Bernouilli model :
>
> -2 log lik = -2 sum (y*log phat + (1-y)*log(1-phat) ), with "phat" is
> the probaility (between 0 and 1) and "y" is the observed values (0 or 1).
>
> 1) Is anybody can tell me if this formula is statistically true?
This looks correct.
> 2...
2005 Apr 21
9
Using R to illustrate the Central Limit Theorem
Dear All
I am totally new to R and I would like to know whether R is able and
appropriate to illustrate to my students the Central Limit Theorem,
using for instance 100 independent variables with uniform distribution
and showing that their sum is a variable with an approximated normal
distribution.
Thanks in advance,
Paul