Displaying 20 results from an estimated 3000 matches similar to: "convergence in polr"
2012 Sep 26
2
non-differentiable evaluation points in nlminb(), follow-up of PR#15052
This is a follow-up question for PR#15052
<http://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15052>
There is another thing I would like to discuss wrt how nlminb() should
proceed with NAs. The question is: What would be a successful way to
deal with an evaluation point of the objective function where the
gradient and the hessian are not well defined?
If the gradient and the hessian both
2004 Feb 19
0
polr warning message optim
Hello R-users,
I am using polr function in library(MASS). The code I use is the following:
polr(as.ordered(q23p)~.,data=as.data.frame(datapr2))
where datapr2 is a matrix of 63 columns (together with the dependent
variable) and 1665 rows. But I am receiving the warning message Error in
optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...)
I would be very greatfull if anyone
2003 Dec 08
2
R^2 analogue in polr() and prerequisites for polr()
Hi
(1)In polr(), is there any way to calculate a pseudo analogue to the
R^2. Just for use as a purely descriptive statistic of the goodness of
fit?
(2) And: what are the assumptions which must be fulfilled, so that the
results of polr() (t-values, etc.) are valid? How can I test these
prerequisites most easily: I have a three-level (ordered factor)
response and four metric variables.
many
2002 Feb 07
1
newbie question: polr and glm.control
I'm running polr() and getting warning messages from glm.fit(). It seems
reasonable to use glm.control() to turn on the trace and follow what
glm.fit() does when called by polr(); or is it?
glm.control(maxit=10, trace=TRUE)
polr(act~., data=mm)
The glm.control() sets the trace TRUE, but there's no change in the output
from polr().
Many thanks in advance for any help/pointers.
2010 Nov 03
2
bugs and misfeatures in polr(MASS).... fixed!
In polr.R the (several) functions gmin and fmin contain the code
> theta <- beta[pc + 1L:q]
> gamm <- c(-100, cumsum(c(theta[1L], exp(theta[-1L]))), 100)
That's bad. There's no reason to suppose beta[pc+1L] is larger than
-100 or that the cumulative sum is smaller than 100. For practical
datasets those assumptions are frequently violated, causing the
2010 Sep 06
3
likelyhood maximization problem with polr
Dear community,
I am currently trying to fit an ordinal logistic regression model with the
polr function. I often get the same error message :
"attempt to find suitable starting values failed", for example with :
require(MASS)
data(iris)
polr(Species~Sepal.Length+Sepal.Width+Petal.Length+Petal.Width,iris)
(I know the response variable Species should be nominal but I do as levels
2004 Mar 03
7
Location of polr function
Hello
I am running R 1.8.1 on a Windows platform
I am attempting to fit an ordinal logistic regression model, using the
polr function, as described in Venables and Ripley. But when I try
model4 <- polr(ypsxcat~committed + as.factor(sex)
+ as.factor(drugusey) + anycsw + as.factor(sex)*committed
+ as.factor(sex)*as.factor(drugusey)+as.factor(sex)*anycsw, data =
duhray)
I get a message
2007 Feb 19
3
summary polr
Hi all,
I have a problem to estimate Std. Error and t-value by ?polr? in library Mass.
They result from the summary of a polr object.
I can obtain them working in the R environment with the following statements:
temp <- polr(formula = formula1, data = data1)
coeff <- summary(temp),
but when the above statements are enclosed in a function, summary reports the following error:
2007 Nov 10
1
polr() error message wrt optim() and vmmin
Hi,
I'm getting an error message using polr():
Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) :
initial value in 'vmmin' is not finite
The outcome variable is ordinal and factored, and the independant variable
is continuous. I've checked the source code for both polr() and optim()
and can't find any variable called
2007 Jun 11
1
How do I obtain standard error of each estimated coefficients in polr
Hi,
I obtained all the coefficients that I need from polr. However, I'm wondering how I can obtain the standard error of each estimated coefficient? I saved the Hessian and do something like summary(polrObj), I don't see any standard error like when doing regression using lm. Any help would be really appreciated. Thank you!
- adschai
2005 Mar 22
1
error with polr()
Dear Sir,
I get an error message when I use polr() in MASS package.
My data is "ord.dat". I made "y" a factor.
y y1 y2 x lx
1 0 0 0 3.2e-02 -1.49485
2 0 0 0 3.2e-02 -1.49485
3 0 0 0 1.0e-01 -1.00000
4 0 0 0 1.0e-01 -1.00000
5 0 0 0 3.2e-01 -0.49485
6 0 0 0 3.2e-01 -0.49485
7 1 1 0 1.0e+00 0.00000
8 0 0 0 1.0e+00 0.00000
9 1 1 0
2007 Jun 04
2
How to obtain coefficient standard error from the result of polr?
Hi - I am using polr. I can get a result from polr fit by calling
result.plr <- polr(formula, data=mydata, method="probit");
However, from the 'result.plr', how can I access standard error of the estimated coefficients as well as the t statistics for each one of them?
What I would like to do ultimately is to see which coefficients are not significant and try to refit the
2003 Feb 25
1
summary(polr.object)
Dear all,
I have used polr in MASS but I am uncertain about the summary(polr.object)
interpretation and would be happy for help on that. This is my summary:
> summary(shade.polr)
Re-fitting to get Hessian
Call:
polr(formula = as.ordered(shade) ~ as.factor(objekt), data = sof,
weights = as.numeric(frek))
Coefficients:
Value Std. Error t value
2.1699520 0.3681840 5.8936612
2011 Mar 01
1
How to understand output from R's polr function (ordered logistic regression)?
I am new to R, ordered logistic regression, and polr.
The "Examples" section at the bottom of the help page for
polr<http://stat.ethz.ch/R-manual/R-patched/library/MASS/html/polr.html>(that
fits a logistic or probit regression model to an ordered factor
response) shows
options(contrasts = c("contr.treatment", "contr.poly"))
house.plr <- polr(Sat ~ Infl +
2000 Mar 11
1
polr question
Dear friends.
Do Polr in Mass change the sign of the coefficients ? Example (McCullagh 1980)
options(contrasts=c("contr.treatment","contr.poly"))
library(Mass)
freq <- c(19,29,24,497,560,269)
yy <- ordered(gl(3,1,6))
z4 <- polr(yy~x,weights=freq)
> z4
Call:
polr(formula = yy ~ x, weights = freq)
Coefficients:
x2
-0.6026492
Intercepts:
1|2
2002 Jun 04
2
machine dependency [polr()/optim()]
Dear R experts:
I am running some calculations using polr() in MASS library, and found some
differences in results obtained on two different machines (IRIX 6.5, and
Linux RH 7.1). It is not clear to me whether this is due to some error in
my programming the calculation and how to resolve the differences, if
possible.
The polr() call is the following:
2009 Jan 13
1
deviance in polr method
Dear all,
I've replicated the cheese tasting example on p175 of GLM's by McCullagh
and Nelder. This is a 4 treatment (rows) by 9 ordinal response (cols)
table.
Here's my simple code:
#### cheese
library(MASS)
options(contrasts = c("contr.treatment", "contr.poly"))
y = c(0,0, 1, 7, 8,8,19, 8,1, 6,9,12,11, 7,6, 1, 0,0, 1,1, 6, 8,23,7,
2012 Jul 09
3
Package 'MASS' (polr): Error in svd(X) : infinite or missing values in 'x'
Hello,
I am trying to run an ordinal logistic regression (polr) using the package
'MASS'.
I have successfully run other regression classes (glm, multinom) without
much problem, but with the 'polr' class I get the following error:
" Error in svd(X) : infinite or missing values in 'x' "
which appears when I run the "summary" command.
The data file is
2004 Oct 09
2
polr problem solved
I'd like to thank John Fox and Chuck Cleland for their help in resovling
this issue. It turned out to be something simple, but perhaps others
have had similar problems
In my original data frame, I had 4 categories of race/ethnicity. One of
the categories (other) was very small, and not similar to any of the
other three categories, so I created a new data frame deleting those
people.
2006 Jul 19
1
Problem with ordered logistic regression using polr function.
Hi,
I'm trying to fit a ordered logistic regression. The response variable
(y) has three levels (0,1,2).
The command I've used is:
/ordlog<-polr(y~x1+x2+x3+x4, data=finalbase, subset=heard, weight=wt,
na.action=na.omit)
/
(There are no NA's in y but there are NA's in X's)
The error I'm getting is:
/Warning messages:
1: non-integer #successes in a binomial glm! in: