Displaying 12 results from an estimated 12 matches for "xcentered".
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2007 Aug 28
1
FW: How to fit an linear model withou intercept
...ry(fitZeroInt)
> # There is a statistically significant difference # between the models -
> the model with and intercetpt, # the "normal" regression is the better
> fit.
> anova(fit1,fit2)
>
> # Center y and x by subtracting their means.
> yCentered<-y-mean(y)
> xCentered<-x-mean(x)
> # Regress the centered y values on the centered x values. This # will
> give us a model with an intercept that is very, very # small. It would
> be zero save for the precision limits # inherent in using a computer.
> Plot the line. Notice the # slope of the centered is t...
2012 Nov 14
3
ctree
Hello,
I plotted a nice tree with "ctree" . It shows 3 nodes with the prediction of
my 2 groups. (see picture)
Unfortunately I need a larger scale to read the exact prediction of my
groups to get the specificity and sensitivity. I tried to change the scale
with "axis" but it didn't work, my guess because it's not a normal graph
with x and y axis.
Has someone an idea
2007 Aug 23
7
Histogram
Hello,
I wanted to create a histogram, but somehow I got stuck...
The interval limits are: x = 1, 2, 3, 3.5, 4.5, 5, 5.5
The interval widths are therefore: 1, 1, 0.5, 1, 0.5, 0.5
Nothing I tried worked... Can anyone help me please?
Thanks
Tobias
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2010 May 04
1
aregImpute (Hmisc package) : error in matxv(X, xcof)...
Dear r-help list,
I'm trying to use multiple imputation for my MSc thesis.
Having good exemples using the Hmisc package, I tried the aregImpute function. But with my own dataset, I have the following error :
Erreur dans matxv(X, xcof) : columns in a (51) must be <= length of b (50)
De plus : Warning message:
In f$xcoef[, 1] * f$xcenter :
la taille d'un objet plus long n'est pas
2008 Aug 13
2
mob(party) formula question
I try tu use mob() with my data.frame ('data.frame': 288 obs. of 81
variables; factors, numerics and ordered factors)
My response is a binary variable and I should use for modelling a logistic
regression (family=binomial).
I read in the "MOB" Vignette that I could use a formula like this if I would
like to have only partitioning variables apart from the response.
2002 Dec 04
1
Interpreting canonical correlation (cancor) results
Hi,
from what I understand about the canonical correlation function
'cancor', it looks for correlations in two sets of variables, each
represented in matrix form. Right? Sounds exactly like what I need.
I have tried the following but I am not sure how to interpret the results.
AudioPCs <- c(ArTHarF0PCA$x[,2], ArTHarF1PCA$x[,2], ArTHarF2PCA$x[,2],
ArTHarF3PCA$x[,2],
2011 Jun 14
0
error message trying to plot survival curves from hypothetical covariate profiles
Dear colleagues,
following John Fox' advice in this article (http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-cox-regression.pdf), I'm trying to create a new data frame to examine the differential survival curves from a combination of covariates.
These are derived from a Cox Proportional Hazards model I fit to data about the diffusion of a particular policy across American
2010 Jun 18
0
Confidence interval calculation for intersection of two quadratic lines
How do I calculate the confidence interval for the value x given by the intersection of two quadratics (i.e. parabolas)?
I fit two quadratics of the form:
y = C1 + B1*x + A1*x^2
y = C2 + B2*x + A2*x^2
to two sets of points N1 and N2.
I test for whether they intersect, if they do then I calculate the roots of:
0 = (C1 - C2) + (B1 - B2)*x + (A1 - A2)*x^2
to determine where they intersect
2003 Mar 27
5
Plot of Canonical Correlation Analysis
Dear all,
I didn't find any graphical solution in the package "mva" to plot the
canonical scores from a CCA (canonical correlation analysis).
Does anybody knows how to plot or has anybody already programmed :
- the map of the canonical scores,
- the graph of the canonical weights,
- the correlation circle i.e. the canonical loadings ?
Thank you for help ...
2009 Apr 22
1
Multiple imputations : wicked dataset ? Wicked computers ? Am I cursed ? (or stupid ?)
Dear list,
I'd like to use multiple imputations to try and save a somewhat badly
mangled dataset (lousy data collection, worse than lousy monitoring, you
know that drill... especially when I am consulted for the first time
about one year *after* data collection).
My dataset has 231 observations of 53 variables, of which only a very
few has no missing data. Most variables have 5-10% of
2010 May 05
0
R-help Digest, Vol 87, Issue 5
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2003 Apr 24
2
R-1.7.0 build feedback: NetBSD 1.6 (PR#2837)
R-1.7.0 built on NetBSD 1.6, but the validation test suite failed:
Machinetype: Intel Pentium III (600 MHz); NetBSD 1.6 (GENERIC)
Remote gcc version: gcc (GCC) 3.2.2
Remote g++ version: g++ (GCC) 3.2.2
Configure environment: CC=gcc CXX=g++ LDFLAGS=-Wl,-rpath,/usr/local/lib
make[5]: Entering directory `/local/build/R-1.7.0/src/library'
>>> Building/Updating