Displaying 20 results from an estimated 1100 matches similar to: "bug in rpart?"
2009 May 12
1
questions on rpart (tree changes when rearrange the order of covariates?!)
Greetings,
I am using rpart for classification with "class" method. The test data is
the Indian diabetes data from package mlbench.
I fitted a classification tree firstly using the original data, and then
exchanged the order of Body mass and Plasma glucose which are the
strongest/important variables in the growing phase. The second tree is a
little different from the first one. The
2009 Oct 27
1
"ipredknn" - How may I find values?
Hi everybody!
I want to find a closer neighbourins observation. This is my code:
##########################
library(klaR)
library(ipred)
library(mlbench)
data(PimaIndiansDiabetes2)
dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)]
dane[,2]=log(dane[,2])
dane[,1:2]=scale(dane[,1:2])
zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F)
2010 Mar 09
1
create picture (k -the nearest neighbours)
Hi
I want to create a nice picture about my result of k -the nearest neighbours
algorithm. Here is my easy code:
#################################
library(klaR)
library(ipred)
library(mlbench)
data(PimaIndiansDiabetes2)
dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)]
dane[,2]=log(dane[,2])
dane[,1:2]=scale(dane[,1:2])
zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F)
2013 Apr 09
2
R crash
I have a generalized linear model to solve. I used package "geepack". When
I use the correlation structure "unstructured", I get a messeage that- R
GUI front-end has stopped working. Why this happens? What is the solution?
The r codes are as follows:
a<-read.table("d:/bmt.txt",header=T")
2005 Apr 23
1
question about about the drop1
the data is :
>table.8.3<-data.frame(expand.grid( marijuana=factor(c("Yes","No"),levels=c("No","Yes")), cigarette=factor(c("Yes","No"),levels=c("No","Yes")), alcohol=factor(c("Yes","No"),levels=c("No","Yes"))), count=c(911,538,44,456,3,43,2,279))
2009 Jul 28
2
A hiccup when using anova on gam() fits.
I stumbled across a mild glitch when trying to compare the
result of gam() fitting with the result of lm() fitting.
The following code demonstrates the problem:
library(gam)
x <- rep(1:10,10)
set.seed(42)
y <- rnorm(100)
fit1 <- lm(y~x)
fit2 <- gam(y~lo(x))
fit3 <- lm(y~factor(x))
print(anova(fit1,fit2)) # No worries.
print(anova(fit1,fit3)) # Likewise.
print(anova(fit2,fit3)) #
2018 Jan 17
1
Assessing calibration of Cox model with time-dependent coefficients
I am trying to find methods for testing and visualizing calibration to Cox
models with time-depended coefficients. I have read this nice article
<http://journals.sagepub.com/doi/10.1177/0962280213497434>. In this paper,
we can fit three models:
fit0 <- coxph(Surv(futime, status) ~ x1 + x2 + x3, data = data0) p <-
log(predict(fit0, newdata = data1, type = "expected")) lp
2005 Jun 15
1
anova.lme error
Hi,
I am working with R version 2.1.0, and I seem to have run into what looks
like a bug. I get the same error message when I run R on Windows as well as
when I run it on Linux.
When I call anova to do a LR test from inside a function, I get an error.
The same call works outside of a function. It appears to not find the right
environment when called from inside a function. I have provided
2010 Jul 31
2
Is profile.mle flexible enough?
Hi the list,
I am experiencing several issues with profile.mle (and consequently with
confint.mle) (stat4 version 2.9.2), and I have to spend a lot of time to
find workarounds to what looks like interface bugs. I would be glad to
get feedback from experienced users to know if I am really asking too
much or if there is room for improvement.
* Problem #1 with fixed parameters. I can't
2004 Dec 20
2
problems with limma
I try to send this message To Gordon Smyth at smyth at vehi,edu.au but it bounced
back, so here it is to r-help
I am trying to use limma, just downloaded it from CRAN. I use R 2.0.1 on Win XP
see the following:
> library(RODBC)
> chan1 <- odbcConnectExcel("D:/Data/mgc/Chips/Chips4.xls")
> dd <- sqlFetch(chan1,"Raw") # all data 12000
> #
> nzw <-
2011 Sep 12
1
coxreg vs coxph: time-dependent treatment
Dear List,
After including cluster() option the coxreg (from eha package)
produces results slightly different than that of coxph (from survival)
in the following time-dependent treatment effect calculation (example
is used just to make the point). Will appreciate any explaination /
comment.
cheers,
Ehsan
############################
require(survival)
require(eha)
data(heart)
# create weights
2008 Jan 05
1
Likelihood ratio test for proportional odds logistic regression
Hi,
I want to do a global likelihood ratio test for the proportional odds
logistic regression model and am unsure how to go about it. I am using
the polr() function in library(MASS).
1. Is the p-value from the likelihood ratio test obtained by
anova(fit1,fit2), where fit1 is the polr model with only the intercept
and fit2 is the full polr model (refer to example below)? So in the
case of the
2012 Nov 08
2
Comparing nonlinear, non-nested models
Dear R users,
Could somebody please help me to find a way of comparing nonlinear, non-nested
models in R, where the number of parameters is not necessarily different? Here
is a sample (growth rates, y, as a function of internal substrate
concentration, x):
x <- c(0.52, 1.21, 1.45, 1.64, 1.89, 2.14, 2.47, 3.20, 4.47, 5.31, 6.48)
y <- c(0.00, 0.35, 0.41, 0.49, 0.58, 0.61, 0.71, 0.83, 0.98,
2008 Apr 17
1
survreg() with frailty
Dear R-users,
I have noticed small discrepencies in the reported estimate of the
variance of the frailty by the print method for survreg() and the
'theta' component included in the object fit:
# Examples in R-2.6.2 for Windows
library(survival) # version 2.34-1 (2008-03-31)
# discrepancy
fit1 <- survreg(Surv(time, status) ~ rx + frailty(litter), rats)
fit1
fit1$history[[1]]$theta
2009 Apr 28
1
How to read the summary
How can I from the summary function, decide which glm (fit1, fit2 or fit3)
fits to data best? I don't know what to look after, so I would please
explain the important output.
> fit1 <- glm(Y~X, family=gaussian(link="identity"))
> fit2 <- glm(Y~X, family=gaussian(link="log"))
> fit3 <- glm(Y~X, family=Gamma(link="log"))
> summary(fit1)
Call:
2018 Jan 18
1
Time-dependent coefficients in a Cox model with categorical variants
First, as others have said please obey the mailing list rules and turn of
First, as others have said please obey the mailing list rules and turn off html, not everyone uses an html email client.
Here is your code, formatted and with line numbers added. I also fixed one error: "y" should be "status".
1. fit0 <- coxph(Surv(futime, status) ~ x1 + x2 + x3, data = data0)
2. p
2005 Aug 29
1
Different sings for correlations in OLS and TSA
Dear list,
I am trying to re-analyse something. I do have two time series, one
of which (ts.mar) might help explaining the other (ts.anr). In the
original analysis, no-one seems to have cared about the data being
time-series and they just did OLS. This yielded a strong positive
correlation.
I want to know if this correlation is still as strong when the
autocorrelations are taken into account.
2011 Jan 05
1
Comparing fitting models
Dear all,
I have 3 models (from simple to complex) and I want to compare them in order to
see if they fit equally well or not.
From the R prompt I am not able to see where I can get this information.
Let´s do an example:
fit1<- lm(response ~ stimulus + condition + stimulus:condition, data=scrd)
#EQUIVALE A lm(response ~ stimulus*condition, data=scrd)
fit2<- lm(response ~ stimulus +
2010 Feb 26
2
Error in mvpart example
Dear all,
I'm getting an error in one of the stock examples in the 'mvpart' package. I tried:
require(mvpart)
data(spider)
fit3 <- rpart(gdist(spider[,1:12],meth="bray",full=TRUE,sq=TRUE)~water+twigs+reft+herbs+moss+sand,spider,method="dist") #directly from ?rpart
summary(fit3)
...which returned the following:
Error in apply(formatg(yval, digits - 3), 1,
2009 Apr 24
2
prediction intervals (alpha and beta) for model average estimates from binomial glm and model.avg (library=dRedging)
Hi all,
I was wondering if there is a function out there, or someone has written code for making confidence intervals around model averaged predictions (y~á+âx). The model average estimates are from the dRedging library?
It seems a common thing but I can't seem to find one via the search engines
Examples of the models are:
fit1 <- glm(y~ dbh, family = binomial, data = data)
fit2 <-