Displaying 20 results from an estimated 6000 matches similar to: "GAM ordered probit"
2006 Oct 27
0
VGAM package released on CRAN
Dear useRs,
upon request, the VGAM package (currently version 0.7-1) has been
officially released on CRAN (the package has been at my website
http://www.stat.auckland.ac.nz/~yee/VGAM for a number of years now).
VGAM implements a general framework for several classes of
regression models using iteratively reweighted least squares
(IRLS). The key ideas are Fisher scoring, generalized linear
and
2012 Apr 04
0
multivariate ordered probit regression---use standard bivariate normal distribution?
Hello.
I have yet to receive a response to my previous post, so I may have
done a poor job asking the question. So, here is the general question:
how can I run a run a multivariate (more than one non-independent,
response variables) ordered probit regression model? I've had success
doing this in the univariate case using the vglm() function in the
VGAM package. For example:
2012 Mar 21
0
multivariate ordinal probit regression vglm()
Hello, all.
I'm investigating the rate at which skeletal joint surfaces pass
through a series of ordered stages (changes in morphology). Current
statistical methods in this type of research use various logit or
probit regression techniques (e.g., proportional odds logit/probit,
forward/backward continuation ratio, or restricted/unrestricted
cumulative probit). Data typically include the
2007 Jun 29
0
GAM for censored data? (survival analysis)
First let me admit that I am no statistician... rather, an ecologist with
just enough statistical knowledge to be dangerous.
I've got a dataset with percent ground cover values for species and other
entities. The data are left censored at zero, in that percent ground cover
cannot be negative. (My data rarely reach 100% cover so I haven't bothered
with adding a right censoring at 100).
2008 Jan 03
1
GLM results different from GAM results without smoothing terms
Hi, I am fitting two models, a generalized linear model and a generalized
additive model, to the same data. The R-Help tells that "A generalized
additive model (GAM) is a generalized linear model (GLM) in which the linear
predictor is given by a user specified sum of smooth functions of the
covariates plus a conventional parametric component of the linear
predictor." I am fitting the GAM
2002 Jul 29
0
multinomial probit
Is there any library for fitting multinomial probit using either likelihood
or the "method of simulated moments" or both.
I presume it would be possible to write a family function in VGAM for the
multinomial probit, but was hoping that someone has done it already.
Thanking you as always.
Vumani Dlamini
CSO-Swaziland
2008 Jun 05
1
GAM hurdle models
Hello,
I have been using mgcv to run GAM hurdle models, analyzing
presence/absence data with GAM logistic regressions, and then analyzing
the data conditional on presence (e.g. without samples with no zeros)
with GAMs with a negative binomial distribution.
It occurs to me that using the negative binomial distribution on data
with no zeros is not right, as the negative binomial allows zeros.
2008 Nov 20
1
gam and ordination (vegan and labdsv surf and ordisurf)
I have a general question about using thin plate splines in the surf
and ordisurf routines. My rudimentary knowledge of a gam is that with
each predictive variable there is a different smooth for each one and
then they are added together with no real interaction term (because
they don't handle this well?). Now, If I have two variables that
have a high D^2 score and a low GCV score (I am
2008 Oct 10
0
Problems and bugs in vgam()
Hello R-Users,
I have recently run into several problems using vgam() in the VGAM
package. I am hoping someone might have some solutions...
Briefly, I have been trying to fit GAM models for zero-altered negative
binomial models.
1. When fitting smoothed parameters (e.g. s(X, df=2)) changing the
degrees-of-freedom has no effect on the level of smoothing (e.g. number
of knots for the
2012 Nov 06
1
Ordered probit using clm2
Hi,
I am new in R. I would like to do a ordered probit regression using clm2 (in the ordinal package).
My dependent variable y is the way of payment in M&A: y=0 if the deal is financed by stock only, y=1 if the deal is financed by a mix of cash and stock and y=2 if it is by cash only.
My independent variables are CollateralB, Cashavailable and Leverage.
This is the code I wrote:
>
2005 Sep 01
1
controlling where *.Rout gets printed. Possible?
OK, my journey to make lab machines automagically install & update all
desirable R packages is nearing an end! The only question I have now is
this: How can I control where the system prints the *.Rout file that is
created automatically when the R batch program runs. In "man R" I don't
find any information about it. When the cron job runs "R_installAll.sh"
(see
2004 Jun 12
2
ordered probit or logit / recursive regression
> I make a study in health econometrics and have a categorical
> dependent variable (take value 1-5). I would like to fit an ordered
> probit or ordered logit but i didn't find a command or package who
> make that. Does anyone know if it's exists ?
R is very fancy. You won't get mundane things like ordered probit off
the shelf. (I will be very happy if someone will show
2008 Nov 14
0
VGAM package released on CRAN
Dear Prof. Thomas Yee
I$B!G(Bm very interested in your R program VGAM.
I tried below your data:
# Nonparametric proportional odds model
data(pneumo)pneumo = transform(pneumo,
let=log(exposure.time))vgam(cbind(normal,mild,severe) ~ s(let),
cumulative(par=TRUE), pneumo)
However, the results by Version of VGAM are different;
----------The result by Version 0.7-7
2013 Jan 21
1
Ordered Probit/Logit with random coefficients
Hello,
I searched everywhere but I didn't find what I want, that is why I as the
question here. Threads discussing this issue on this mailing list are
already quite old. Does anybody know of a function in R which allows to
estimate ordered probit/logit model with random coefficients.
The only mixed effect model I found was clmm of the ordinal package but it
only provides random intercepts. I
2008 Apr 18
2
rzinb (VGAM) and dnbinom in optim
Dear R-help gurus (and T.Yee, the VGAM maintainer) -
I've been banging my head against the keyboard for too long now, hopefully someone can pick up on the errors of my ways...
I am trying to use optim to fit a zero-inflated negative binomial distribution. No matter what I try I can't get optim to recognize my initial parameters. I think the problem is that dnbinom allows either
2006 Apr 05
2
Problems in package management after Linux system upgrade
I upgraded from Fedora Core 4 to Fedora Core 5 and I find a lot of
previously installed packages won't run because shared libraries or
other system things have changed "out from under" the installed R
libraries. I do not know for sure if the R version now from
Fedora-Extras (2.2.1) is exactly the same one I was using in FC4.
I see problems in many packages. Example, Hmisc:
unable
2011 Mar 11
0
variance explained by each term in a GAM
Picking up an ancient thread (from Oct 2007), I have a somewhat more complex
problem than given in Simon Wood's example below. My full model has more than
two smooths as well as factor variables as in this simplified example:
b <- gam(y~fv1+s(x1)+s(x2)+s(x3))
Judging from Simon's example, my guess is to fit reduced models to get
components of deviance as follows:
b1 <-
2008 May 06
1
mgcv::gam shrinkage of smooths
In Dr. Wood's book on GAM, he suggests in section 4.1.6 that it might be
useful to shrink a single smooth by adding S=S+epsilon*I to the penalty
matrix S. The context was the need to be able to shrink the term to zero if
appropriate. I'd like to do this in order to shrink the coefficients towards
zero (irrespective of the penalty for "wiggliness") - but not necessarily
all the
2003 Jun 05
1
partial residuals in plot.gam()
All,
Sorry for bombarding you with GAM related questions, but...
I know a partial residual option in plot.gam() is on Simon Wood's todo
list, but since I'm in the midst of a project and not yet having acquired
sufficient R knowledge to code something usable myself I'll have to put my
trust in you. Anybody got some code lying around for doing this? Or if
someone can supply me with
2003 May 26
0
knots fixed in gam(), library(mgcv)
Dear all,
I have a problem with specifying the no. of knots in our function which
include gam(). I last worked with this in mid September but since then I
have reinstalled R and Simon Wood's library(mgcv), which he has changed
since then. The statistician (and good R-coder) with whom I co-operate is
now unfortunately overloaded with teaching, and I'm in the sprut of my
thesis.... I