Displaying 20 results from an estimated 5000 matches similar to: "Avoiding singular fits in rlm"
2011 Mar 14
1
discrepancy between lm and MASS:rlm
Dear R-devel,
There seems to be a discrepancy in the order in which lm and rlm evaluate their arguments. This causes rlm to sometimes produce an error where lm is just fine.
Here is a little script that illustrate the issue:
> library(MASS)
> ## create data
> n <- 100
> dat <- data.frame(x=rep(c(-1,0,1), n), y=rnorm(3*n))
>
> ## call lm, works fine
> summary(lm(y ~
2008 May 14
1
rlm and lmrob error messages
Hello all,
I'm using R2.7.0 (on Windows 2000) and I'm trying do run a robust
regression on following model structure:
model = "Y ~ x1*x2 / (x3 + x4 + x5 +x6)"
where x1 and x2 are both factors (either 1 or 0) and x3.....x6 are numeric.
The error code I get when running rlm(as.formula(model), data=daymean) is:
error in rlm.default(x, y, weights, method = method, wt.method =
2010 Aug 17
0
Singular error in rlm
I am absolutely new to R and I am aware of only a few basic command lines. I
was running a robust regression in R, using the following command line
library (MASS)
rfmodel2 <- rlm (TotalEmployment_2005 ~ ALABAMA + MISSISSIPPI + LOUISIANA +
TotalEmployment_2000 + PCWhitePop_2005 + UnemploymentRate_2005 +
PCUrbanPop2000 + PCPeopleWithACollegeDegree_2000 +
2010 Dec 13
1
Wrong contrast matrix for nested factors in lm(), rlm(), and lmRob()
This message also reports wrong estimates produced by lmRob.fit.compute()
for nested factors when using the correct contrast matrix.
And in these respects, I have found that S-Plus behaves the same way as R.
Using the three available contrast types (sum, treatment, helmert)
with lm() or lm.fit(), but just contr.sum with rlm() and lmRob(),
and small examples, I generated contrast matrices for
2005 Mar 24
1
Robust multivariate regression with rlm
Dear Group,
I am having trouble with using rlm on multivariate data sets. When I
call rlm I get
Error in lm.wfit(x, y, w, method = "qr") :
incompatible dimensions
lm on the same data sets seem to work well (see code example). Am I
doing something wrong?
I have already browsed through the forums and google but could not find
any related discussions.
I use Windows XP and R
2010 Nov 08
1
Add values of rlm coefficients to xyplot
Hello,
I have a simple xyplot with rlm lines.
I would like to add the a and b coefficients (y=ax+b) of the rlm calculation
in each panel.
I know I can do it 'outside' the xyplot command but I would like to do all
at the same time.
I found some posts with the same question, but no answer.
Is it impossible ?
Thanks in advance for your help.
Ptit Bleu.
x11(15,12)
xyplot(df1$col2 ~
2003 Oct 02
4
using a string as the formula in rlm
Hi,
I am trying to build a series of rlm models. I have my data frame and
the models will be built using various coulmns of the data frame.
Thus a series of models would be
m1 <- rlm(V1 ~ V2 + V3 + V4, data)
m2 <- rlm(V1 ~ V2 + V5 + V7, data)
m3 <- rlm(V1 ~ V2 + V8 + V9, data)
I would like to automate this. Is it possible to use a string in place
of the formula?
I tried doing:
fmla
2012 Jul 06
1
How to do goodness-of-fit diagnosis and model checking for rlm in R?
Hi all,
I am reading the MASS book but it doesn't give examples about the diagnosis
and model checking for rlm...
My data is highly non-Gaussian so I am using rlm instead of lm.
My questions are:
0. Are goodness-of-fit and model-checking using rlm completely the same as
usual regression?
1.
Please give me some pointers about how to do goodness-of-fit and
residual diagnosis for
2008 Dec 08
1
residual standard error in rlm (MASS package)
Hi,
I would appreciate of someone could explain how the residual standard
error is computed for rlm models (MASS package). Usually, one would
expect to get the residual standard error by
> sqrt(sum((y-fitted(fm))^2)/(n-2))
where y is the response, fm a linear model with an intercept and slope
for x and n the number of observations. This does not seem to work for
rlm models and I am wondering
2004 Oct 11
3
split and rlm
Hello, I'm trying to do a little rlm of some data that looks like this:
UNIT COHORT perdo adjodds
1010 96 0.39890 1.06894
1010 97 0.48113 1.57500
1010 98 0.36328 1.21498
1010 99 0.44391 1.38608
It works fine like this: rlm(perdo ~ COHORT, psi=psisquare)
But the problem is that I have about 100 UNITs, and I want to do a
2008 Jan 19
1
How do we get two-tailed p-values for rlm?
How do we get 2-tailed p-values for the rlm summary?
I'm using the following:
> fit <- rlm(oatRT ~ oatoacData$erp, psi=psi.bisquare, maxit=100,
na.action='na.omit')
> fitsum <- summary(fit, cor=F)
> print(fitsum)
Call: rlm(formula = oatRT ~ oatoacData$erp, psi = psi.bisquare, maxit = 100,
na.action = "na.omit")
Residuals:
Min 1Q Median
2012 Jul 18
1
How does "rlm" in R decide its "w" weights for each IRLS iteration?
Hi all,
I am also confused about the manual:
a. The input arguments:
wt.method are the weights case weights (giving the relative importance of
case, so a weight of 2 means there are two of these) or the inverse of the
variances, so a weight of two means this error is half as variable?
w (optional) initial down-weighting for each case.
init (optional) initial values for the
2004 Apr 07
4
Problems with rlm
Dear all,
When calling rlm with the following data, I get an error. (R v.1.8.1,
WinXP Pro 2002 with service pack 1.)
> d <- na.omit(data.frame(CPRATIO, HEIGHTZ, FAMILYID))
> c <- tapply(d$CPRATIO, d$FAMILYID, mean)
> h <- tapply(d$HEIGHTZ, d$FAMILYID, mean)
> c
1 2 3 6 7 9 10
11
6.000000 2.500000 3.250000
2007 Jun 07
3
rlm results on trellis plot
How do I add to a trellis plot the best fit line from a robust fit? I
can use panel.lm to add a least squares fit, but there is no panel.rlm
function.
--
Alan S Barnett <asb at mail.nih.gov>
NIMH/CBDB
2005 Mar 27
1
p values when using rlm
R 2.0.1
Linux
I am using rlm() to fit a model, e.g. fit1<-rlm(y~x). My model is more
complex than the one shown.
When I enter summary(fit1)
I get estimates for the model's coefficients along with their SEs, and
t values, but no p values. The p value column is blank.
Similarly, when I enter anova(fit1) I get DF, Sum Sq, Mean Sq, but the
column for F value and Pr(>F) are blank.
Any
2005 Feb 25
1
vcov on result of rlm() yields "-- please report!" (PR#7707)
Dear r-bugs,
I looked over the FAQ. Hope I'm reporting this correctly.
I ran this on both solaris and windows. I've provided terminal snapshots
which include how R was called from the command line, and the
result of version at the R prompt.
I have attached the .r file, and the data file and the output snapshots.
Below also find everything except only a few lines of the data file.
Note
2006 May 20
1
ANCOVA, Ops.factor, singular fit???
I'm trying to perform ANCOVAs in R 1.14, on a Mac OS X, but I can't figure out
what I am doing wrong. Essentially, I'm testing whether a number of
quantitative dental measurements (the response variables in each ANCOVA) show
sexual dimorphism (the sexes are the groups) independently of the animal's size
(the concomitant variable). I have attached a 13-column matrix as a data
2010 Jul 12
1
Robust regression error: Too many singular resamples
Hello.
I've got a dataset that may have outliers in both x and y. While I am not
at all familiar with robust regression, it looked like the function lmrob in
package robustbase should handle this situation. When I try to use it, I
get:
Too many singular resamples
Aborting fast_s_w_mem()
Looking into it further, it appears that for an indicator variable in one of
my interaction terms, 98%
2003 Jul 30
2
robust regression
Hi,
trying to do a robudt regression of a two-way linear model, I keep
getting the following error:
> lqs(obs ~ y + s -1,method="lms", contrasts=list(s=("contr.sum")))
Error: lqs failed: all the samples were singular
Robust regression with M-estimators works (also regular least square
fits, of course):
rlm.formula(formula = obs ~ y + s - 1, method = "M",
2004 Jun 11
1
comparing regression slopes
Dear List,
I used rlm to calculate two regression models for two data sets (rlm
due to two outlying values in one of the data sets). Now I want to
compare the two regression slopes. I came across some R-code of Spencer
Graves in reply to a similar problem:
http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html
The code was:
> df1 <- data.frame(x=1:10, y=1:10+rnorm(10))