Displaying 20 results from an estimated 8000 matches similar to: "glm: family=exponential() or family=Gamma(alpha=1)?"
2008 Jun 08
1
exponential distribution
Dear all,
I've tried to solve the Es. 12, cap 4 of "Introduction to GLM" by Annette Dobson.
It's about the relationship between survival time of leukemia patients and blood cell count.
I tried to fit a model with exponential distribution, first by glm (family gamma and then dispersion parameter fixed to 1) and
then with survreg.
They gave me the same point estimates but the
2004 Mar 23
1
influence.measures, cooks.distance, and glm
Dear list,
I've noticed that influence.measures and cooks.distance gives different
results for non-gaussian GLMs. For example, using R-1.9.0 alpha
(2003-03-17) under Windows:
> ## Dobson (1990) Page 93: Randomized Controlled Trial :
> counts <- c(18,17,15,20,10,20,25,13,12)
> outcome <- gl(3,1,9)
> treatment <- gl(3,3)
> glm.D93 <- glm(counts ~ outcome +
2003 Jun 10
2
fitting data to exponential distribution with glm
I am learning glm function, but how do you fit data using exponential
distribution with glm?
In the help file, under "Family Objects for Models", no ready made option
seems available for the distribution as well as for other distributions
satisfying GLM requirements not listed there.
2000 Apr 19
1
scale factors/overdispersion in GLM: possible bug?
I've been poking around with GLMs (on which I am *not* an expert) on
behalf of a student, particularly binomial (standard logit link) nested
models with overdispersion.
I have one possible bug to report (but I'm not confident enough to be
*sure* it's a bug); one comment on the general inconsistency that seems to
afflict the various functions for dealing with overdispersion in GLMs
2012 Sep 25
1
appropriate test in glm when the family is Gamma
Dear R users,
Which test is most appropriate in glm when the family is Gamma?
In the help page of anova.glm, I found the following
?For models with known dispersion (e.g., binomial and Poisson fits) the chi-squared test is most appropriate, and for those with dispersion estimated by moments (e.g., gaussian, quasibinomial and quasipoisson fits) the F test is most appropriate.?
My questions :
2009 Jul 15
1
GLM Gamma Family logLik formula?
Hello all,
I was wondering if someone can enlighten me as to the difference
between the logLik in R vis-a-vis Stata for a GLM model with the gamma
family.
Stata calculates the loglikelihood of the model as (in R notation)
some equivalent function of
-1/scale * sum(Y/mu+log(mu)+(scale-1)*log(Y)+log(scale)+scale*lgamma(1/scale))
where scale (or dispersion) = 1, Y = the response variable, and mu
1999 Apr 19
1
Algorithm used by glm, family=binomial?
Does anyone know what algorithm R uses in glm, family=binomial (i.e. a
logit model)?
I assume that it's in the source somewhere, but I wasn't able to find
it. I'd like to know
what file it's in (in a unix distribution of R).
Thanks for your help.
---------------------------
Barnet Wagman
wagman at enteract.com
1361 N. Hoyne, 2nd floor
Chicago, IL 60622
773-645-8369
2012 Sep 15
1
Interpretation of result in R
I am trying to do a quasipoisson regression to know if the frequency of
drinking of my subject is related to temperature. The problem is that I'm
not sure how to interpret my result.
1) Since my result is signifiant, can I tell that the frequency of drinking
of my subject increase linearly or exponentially?
2) When I want to quantify the increase, do I need to do an exponential
2002 Nov 24
1
Understanding function residuals()
Hello:
I am trying to understand why glm() does not replicate the results in
Dobson, "Introduction to Generalized Linear Models," pp. 17-20.
I set up the following model. The variable CONDT is assumed as Poisson and
the objective is to estimate the expected value.
The data (chronic medical conditions among women in Australia) is as
follows:
CONDT <- c(0, 1, 1, 0, 2, 3, 0, 1,
1998 Aug 28
1
R-beta: repeated measures GLM binomial data?
I don't know much about GLM in general or glm in R. Can anyone tell me
how to do the following (in R or some other stat system) or refer me to a
textbook discussion?
Two factor ANOVA repeated measures design.
Each subject gives a percent correct.
I am assuming the correct way to proceed is to fit a generalized linear
model with binomial responses and logistic link. But I have not found a
2005 Jul 20
4
HOWTO capture digits
Folks:
does anybody have an idea? how to capture the DTMF digits to a file, after
an extn asnwer? then POST it to a url?
Regards,
JR
2001 Oct 23
1
FTP-Access from R
I want to access a file on a ftp-server with R. But it doesn't work. I
suppose the reason is the username and password. Here the non working
file path
ftp://woudc:woudc*@ftp.tor.ec.gc.ca/Archive-NewFormat/totalozone_1.0_1/stn035/dobson/1929/19290301.dobson.beck.002.smi.csv
I tested other files on this server, same result: a crash of R. I tested
it with other 'normal' sites (on other
2013 May 29
1
quick question about glm() example
I don't have a copy of Dobson (1990) from which the glm.D93 example is
taken in example("glm"), but I'm strongly suspecting that these are
made-up data rather than real data; the means of the responses within
each treatment are _identical_ (equal to 16 2/3), so two of the
parameters are estimated as being zero (within machine tolerance). (At
this moment I don't understand
2007 May 25
1
Estimation of Dispersion parameter in GLM for Gamma Dist.
Hi All,
could someone shed some light on what the difference between the
estimated dispersion parameter that is supplied with the GLM function
and the one that the 'gamma.dispersion( )' function in the MASS
library gives? And is there consensus for which estimated value to
use?
It seems that the dispersion parameter that comes with the summary
command for a GLM with a Gamma dist. is
2000 Jan 31
2
glm
I've downloaded R for windows (9.0.1) and it is great! I've
converted all my lecture notes for my GLM course to run on R (they are
available on my web page below). I must admit I particularly like the
default contrast options, which are identical to GLIM. Also I like the
gl function - very useful! I have a couple of questions/bugs:
1. predict.glm doesn't work, but predict.lm does -
2005 Aug 10
2
Exponential, Weibull and log-logistic distributions in glm()
Dear R-users!
I would like to fit exponential, Weibull and log-logistic via glm() like
functions. Does anyone know a way to do this? Bellow is a bit longer
description of my problem.
Hm, could family() be adjusted/improved/added to allow for these distributions?
SAS procedure GENMOD alows to specify deviance and variance functions to
help in such cases. I have not tried that option and I do not
2000 Jun 25
1
possible bug, anova.glm(), family="gaussian" (PR#579)
Dear R team,
I don't get what I think I should get when using anova.glm() with
family="gaussian" -- please ignore this and forgive me if this turns out
to be another example of a fundamental misunderstanding on my part (a
highly likely event!) For example:
S <- as.factor(rep(c(rep("m",2),rep("f",2)),2))
A <-
2005 Mar 25
3
800 numbers and FWD
Guys.
Can you dial 800 and 888 toll free numbers using FWD? how do you dial them
cause I tried using 1800xxxxx and 1888xxxxx and I simply get a "nobody can
asnwer the call" signal on asterisk.
Can you dial 800 toll free from FWD?
2008 Oct 27
1
Exponential regression (Y = exp(a*X)) and standard error of Ŷi
r-help at lists.R-project.org
?
Hello
?
First I want to implement exponential regression in R, with out constant for the following formula.
Y = exp(a*X)
?a? is coefficient I wanted to determine. That I could do also in SPSS but my question is rather to estimate the ?standard error of ??i ?at each Xi. This is called in SPSS ?satndard error of mean prediction? or generally known for non-linear
2006 Mar 05
1
glm gives t test sometimes, z test others. Why?
I just ran example(glm) and happened to notice that models based on
the Gamma distribution gives a t test, while the Poisson models give a
z test. Why?
Both are b/s.e., aren't they?
I can't find documentation supporting the claim that the distribution
is more like t in one case than another, except in the Gaussian case
(where it really is t).
Aren't all of the others approximations