Displaying 20 results from an estimated 55 matches for "0.242".
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0.22
2005 Feb 15
3
using poly in a linear regression in the presence of NA f ails (despite subsetting them out)
This smells like a bug to me. The error is triggered by the line:
variables <- eval(predvars, data, env)
inside model.frame.default(). At that point, na.action has not been
applied, so poly() ended being called on data that still contains missing
values. The qr() that issued the error is for generating the orthogonal
basis when evaluating poly(), not for fitting the linear model itself.
2005 Feb 15
3
using poly in a linear regression in the presence of NA f ails (despite subsetting them out)
This smells like a bug to me. The error is triggered by the line:
variables <- eval(predvars, data, env)
inside model.frame.default(). At that point, na.action has not been
applied, so poly() ended being called on data that still contains missing
values. The qr() that issued the error is for generating the orthogonal
basis when evaluating poly(), not for fitting the linear model itself.
2007 Jan 23
3
the value of Delta
Dear all,
I am running R 2.4.1.
> library(siggenes);
> library(multtest);
> cl<-rep(c(0,1),c(3,3));
> sub<-exprs(AffyExpData[,c(1:3,7:9)]);
> gn<-geneNames(AffyRAwData);
> sam.out<-sam(sub,cl,rand=123,gene.names=gn);
We're doing 20 complete permutations
> sam.out
SAM Analysis for the Two-Class Unpaired Case Assuming Unequal Variances
Delta p0
2009 Aug 11
3
loadings function (PR#13886)
Full_Name: Mike Ulrich
Version: 2.9
OS: Mac OSX
Submission from: (NULL) (69.169.178.34)
The help documentation for loadings() lists more then one parameter. The
function call only expects one parameter. The digits, cutoff, and sort
parameters are not used in the function.
## S3 method for class 'loadings':
print(x, digits = 3, cutoff = 0.1, sort = FALSE, ...)
## S3 method for class
2005 Feb 14
0
using poly in a linear regression in the presence of NA fails (despite subsetting them out)
I ran into a to me surprising result on running lm with an orthogonal
polynomial among the predictors.
The lm command resulted in
Error in qr(X) : NA/NaN/Inf in foreign function call (arg 1)
Error during wrapup:
despite my using a "subset" in the call to get rid of NA's.
poly is apparently evaluated before any NA's are subsetted out
of the data.
Example code (attached to
2008 Aug 08
2
Truncation error on simply mean & sum function (PR#12515)
Full_Name: Tom Wang
Version: 2.6.2
OS: Linux, Windows
Submission from: (NULL) (61.230.6.228)
I've found an instance:
> a <- c(0.187,-0.019,0.074,-0.06,0.221,-0.079,0.12,0.079,-0.281,-0.242)
> sum(a)
[1] -2.428613e-17
The actual sum is 0 but it reports the wrong answer.
Maybe it is due to the computer truncation error.
2012 Jul 22
2
Frame Column to List (conversion)
Hi,
Input Format: excel file (XLS)
Column 1: Gene ID (alphanumeric)
Column 2 - 10 : (numeric data).
inData = read.xls ( <fileName>)
geneLabel = inData [ , 1] - column 1 stored in geneLabel
tempData = inData [ , 2: 10]
expValues = data.matrix (tempData) - convert frame into Matrix format
expValues has the matrix format needed for analysis.
I need to bind gene labels as .
I
2012 Dec 14
1
format.pval () and printCoefmat ()
Hi List,
My goal is to force R not to print in scientific notation in the sixth column (rel_diff - for the p-value) of my data frame (not a matrix).
I have used the format.pval () and printCoefmat () functions on the data frame. The R script is appended below.
This issue is that use of the format.pval () and printCoefmat () functions on the data frame gives me the desired results, but coerces
2009 Mar 31
3
Factor Analysis Output from R and SAS
Dear Users,
I ran factor analysis using R and SAS. However, I had different outputs from
R and SAS.
Why they provide different outputs? Especially, the factor loadings are
different.
I did real dataset(n=264), however, I had an extremely different from R and
SAS.
Why this things happened? Which software is correct on?
Thanks in advance,
- TY
#R code with example data
# A little
2010 Feb 04
2
help needed using t.test with factors
I am trying to use t.test on the following data:
date type INTERVAL nCASES MTF SDF MTO SDO
nFST MF nOBS MO MB BIASCV BIASEV ME MAE
RMSE CRCF
2001-06-15 avn GE1.00 4385 0.246 0.300 1.502
0.556 1367 1.373 4385 1.502 1.471 0.285 0.164
-1.256 1.266 1.399 0.056
2001-06-15 avn
2019 Oct 18
1
Dovecot v2.3.8 released
> On 18/10/2019 14:25 Tom Sommer via dovecot <dovecot at dovecot.org> wrote:
>
>
> On 2019-10-08 13:18, Aki Tuomi via dovecot wrote:
> > https://dovecot.org/releases/2.3/dovecot-2.3.8.tar.gz
> > https://dovecot.org/releases/2.3/dovecot-2.3.8.tar.gz.sig
> > Binary packages in https://repo.dovecot.org/
>
> > - imap: SETMETADATA with literal value
2004 Jan 12
1
extract data from a data.frame
Hi,
I'm reading part of a table from postgres, so I'm
getting a data frame.
how can I extract the numerica values so I can
operate on them.
> res <- dbGetResult(mydata)
> str(res)
`data.frame': 5 obs. of 8 variables:
$ cyx.1: num 0.149 -0.278 0.114 0.060 0.109
$ cyx.2: num 0.158 -0.070 0.063 0.149 0.150
$ cyx.3: num 0.052 -0.350 0.114 0.126 0.238
2006 Feb 24
1
Extracting information from factanal()
Dear list members,
I apologize for putting this (probably) very basic question on the
mailing list. I have scanned through the R website (using search) but
did not found an answer.
(code included below)
A factor matrix is simply extracted (which can then subsequently be
exported using write.table) by FACT$loadings[1:6,].
I would also like to specifically extract and export
2010 Oct 04
2
Plot for Binomial GLM
Hi i would like to use some graphs or tables to explore the data and make
some sensible guesses of what to expect to see in a glm model to assess if
toxin concentration and sex have a relationship with the kill rate of rats.
But i cant seem to work it out as i have two predictor
variables~help?Thanks.:)
Here's my data.
>
2004 Nov 30
1
Info
I am having difficulty obtaining the scores from my principal component
analysis. I have used this method before and have had no problems. The
data set that I am using this time is similar to what I have used in the
past. What do I need to do to my dataset in order for me to obtain these
scores?
R screen says the following message
Error in factanal(covmat = pasa.cov, factors = 4) :
2012 Mar 29
1
abline with xyplot does not work
I am trying to plot the results of a random effects model where each subject is allowed to have his, or her, own intercept. I use xyplot to plot the data, lme to compute the regression and then try to put a summary regression line on the xyplot. As can be seen by the output pasted below, I am getting an error message,
Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) :
(list)
2006 Apr 27
1
Plotting Data Frame
Dear R community members,
I think I am asking a very simple question, but I really looked up in
the faqs and manuals and found nothing helpful.
I am trying to plot a data frame with the following structure (this is
just a small extract):
glo conc odor line series X1 X2 X3 X4 X5
X6 X7 X8 X9 X10 X11 X12 X13
1 0 AIR LN1 UP -0.488
2003 Jan 20
1
make check for R-1.6.2 on IBM AIX
Dear all,
The 'make check' step fails for the pacakge mva on IBM AIX.
The tail of the Rout log file looks like:
> for(factors in 2:4) print(update(Harman23.FA, factors = factors))
Call:
factanal(factors = factors, covmat = Harman23.cor)
Uniquenesses:
height arm.span forearm lower.leg weight
0.170 0.107 0.166
2010 Feb 09
2
Double Integral Minimization Problem
Hello all,
I am trying to minimize a function which contains a double integral, using
"nlminb" for the minimization and "adapt" for the integral. The integral is
over two variables (thita and radiusb)
and the 3 free parameters I want to derive from the minimization are
counts0, index and radius_eff.
I have used both tasks in the past successfully but this is the first time
2008 Mar 25
1
Subset of matrix
Dear R users
I have a big matrix like
6021 1188 790 290 1174 1015 1990 6613 6288
100714
6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32
0.252 0.206
1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194
0.168 0.171
790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19
0.171 0.174
290 0.474