search for: xcenter

...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...

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

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 -- View this message in context: http://www.nabble.com/Histogram-tf4315900.html#a12288850 Sent from the R help mailing list archive at Nabble.com.

...e 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 multiple de la taille d'un objet plus court   = longer object length is not a multiple of shorter object length I first tried to "I()" all the continuous variables but the same error occurs with different numbers : Erreur dans matx...

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.

...[,4] [,5] [1,] -0.018006 -0.074138 -0.038670 0.0072364 0.082370 [2,] -0.293414 -0.176453 -0.015322 -0.0111357 -0.072555 [3,] 0.179000 0.048471 -0.103974 0.3313531 -0.049797 [4,] -0.126606 -0.088371 0.214449 -0.2998246 0.063524 [5,] 0.133073 0.011817 -0.073828 -0.0278944 -0.081489 $xcenter [1] 1.9984e-16 2.2177e-15 -7.5495e-16 -2.6312e-15 1.5543e-16 $ycenter [1] -5.5511e-17 1.4683e-15 -3.1086e-16 -1.9984e-16 -3.5527e-16 So in this example, I took the second principal components each from a bunch of variables, stuck them together in matrices and then performed CCA on it. The...

...construct a data frame with a hypothetical covariate profile: n<-data.frame(news=rep(c(1,4,8)), evstatus=as.factor(1:3), enviro=mean(newdat$enviro), partisan=c("democrat", "mixed", "republican")) plot(survfit(mymod1, newdata=n)) Error in scale.default(x2, center = xcenter, scale = FALSE) : length of 'center' must equal the number of columns of 'x' I've looked and someone encountered a similar error trying to plot predicted values from a stepwise regression. That issue did not appear to be solved. On the surface of it it seems that I need to...

...ell modelled at room temperature. By inspection of ~4,000 plots of device data I see that there is sometimes a linear dependence and sometimes a dependence with curvature adequately represented by a quadratic fit. The zero temperature device behavior is given by ( (y-yoffset)/yscale )^(2/3) + ( (x-xcenter)/xscale )^(2/3) = 1 which is darn hard to fit with linear models even for perfect devices, which we do not have. The room temperature device behavior is so poorly understood that it is only simulated with finite element models, which does not give me a neat analytic expression such as p^(2/3) + q^...

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 ...

...39;s aregImpute (in package Hmisc) : > system.time(DataTest.arI<-aregImpute(~ctr+cadredp+persmob+trea+taller +tbox+nbpradio+nbpventil+sitrea,data=DataTest,n.impute=5)) Erreur dans matxv(X, xcof) : columns in a (35) must be <= length of b (33) De plus : Warning message: In f$xcoef[, 1] * f$xcenter : la taille d'un objet plus long n'est pas multiple de la taille d'un objet plus court Timing stopped at: 0.028 0 0.028 > Examples #1 and #2 of the manual gave expected results. Package "mi" (Andrew Gelman and a Columbia team, early development (version=0.06.something...

...e 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 multiple de la taille d'un objet plus court ? = longer object length is not a multiple of shorter object length I first tried to "I()" all the continuous variables but the same error occurs with different numbers : Erreur dans matx...

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