search for: ycentered

...mary(fitNormalReg) > summary(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...

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.

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

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],

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.

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 ...

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