similar to: reversing the x-axis terms on a boxplot

Hi All, I am a PhD student in forestry science and I am working with LiDAR data set (huge data set). I am a brand-new in R and geostatistic (SORRY, my background it?s in forestry) but I wish improve my skill for improve myself. I wish to develop a methodology to processing a large data-set of points (typical in LiDAR) but there is a problem with memory. I had created a subsample data-base but

Getting a very strange error with a new install of R from source on x86; make[3]: Leaving directory `/tmp/R.INSTALL.r20887/cluster/src' ** R ** data ** moving datasets to lazyload DB Error in factor(c(1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1), : invalid labels; length 2 should be 1 or 1 Execution halted ERROR: lazydata failed for package 'cluster' ** Removing

Hi: I have a question making side by side boxplot. My response is numeric and I want to make a side by side boxplot of it accroding to a factor vector. So, there are several boxplots on the same plot. Each boxplot is with respect to one level for a factor. The levels of the factor are some characters. When I make the plot, the boxplots are arranged according to the alphabetic order of the

Hi, Is anyone on the list familiar with an R implementation of Piper Diagrams? Example: http://faculty.uml.edu/nelson_eby/89.315/IMAGES/Figure%209-78.jpg I am thinking that two calls to triax.plot (plotrix) along with some kind of affine-transformed standard plot would do the trick. Not so sure about the final layout, or a nice generalized version for something like lattice. Cheers, Dylan

Hi, I have been trying to use the new .parallel argument with the most recent version of plyr [1] to speed up some tasks. I can run the example in the NEWS file [1], and it seems to be working correctly. However, R will only use a single core when I try to apply this same approach with ddply(). 1. http://cran.r-project.org/web/packages/plyr/NEWS Watching my CPUs I see that in both cases

Greetings, Experimenting with the cluster package, and am starting to scratch my head in regards to the *best* way to standardize my data. Both functions can pre-standardize columns in a dataframe. according to the manual: Measurements are standardized for each variable (column), by subtracting the variable's mean value and dividing by the variable's mean absolute deviation. This

Hi all, I would like to ask a question with regard to R graphics. I am currently trying to add data points in boxplots using points(). In my script, I add up boxplots three times using add=TRUE. I use points() every time I add boxplots, and I see data points. However, I see all data points are clustered at three specific points on x-axis; the locations of the data points are not overlapping with

Hi, I have fit a series of ols() models, by group, in this manner: l <- ols(y ~ rcs(x, 4)) ... where the series of 'x' values in each group is the same, however knots are not always identical between groups. The result is a table of 'coefs' derived from the ols objects, by group: group Intercept top top' top'' 1 6.864 0.01 2.241 -2.65

Hi, I have developed a logistic regression model in the form of (factor_1~ numeric + factor_2) and would like to perform a cross-validation or some similar form of sensitivity analysis on this model. using cv.glm() from the boot package: # dataframe from which model was built in 'z' # model is called 'm_geo.lrm' # as suggested in the man page for a binomial model: cost <-

Greetings, I am trying to add an extra labled axis in position 3 (top x-axis), with numbers that do not match up with the existing axes. Surely this must be possible, and I am just doing it incorectly. So far I have tried the following: #make a plot plot(TIK, type="l", cex=.25, xlim=c(2,32), ylim=c(0,1600)) #try and add a new axis with different numbers in position 3

Greetings: As I am not a windows user, I cannot try this: is it possible to install rgdal on windows without having to compile it from source ? Compilation on MacOS is within my abilities, however each time i try and install the rgdal package it dies complaining that it cannot find gdal-config --- which was recently installed with GRASS. I have updated my PATH environment variable, logged

Hi, I am trying to use quantile regression to perform weighted-comparisons of the median across groups. This works most of the time, however I am seeing some odd output in summary(rq()): Call: rq(formula = sand ~ method, tau = 0.5, data = x, weights = area_fraction) Coefficients: Value Std. Error t value Pr(>|t|) (Intercept) 45.44262 3.64706 12.46007

Hello there, could somebody help me with this: I have to create a lot of boxplots but with same range concerning the x-axis. For example I have following data: liste1 <- c(3,4,5,3,3,4,4) liste2 <- c(1,2,3,4,6) png(file = "liste1.png") boxplot(liste1) png(file = "liste2.png") boxplot(liste2) q() Works perfectly, but what I need would be that both boxplots have their

Hi, Is there a simple way to suppress the plotting of polygon boundaries with spplot() ? # simple list of 12 colors cols <- brewer.pal(12, "Paired") # plot pile of polygons, with 12 classes: spplot(x, zcol='class2', col.regions=cols, scales=list(draw=T), xlab="Easting (m)", ylab="Northing (m)") ... seems to work well. However the polygon boundaries

Hi, I am using the rcs() function in the Design library to model non-linearity that is not well characterized by an otherwise mechanistic function. I am able to make the model 'available' to others through the excellent nomogram() function and the set of tables that it can create. However, I would like to present the model in an 'expanded' format-- probably what rcspline.restate()

Hi, Is there any way to suppress plotting of panels that don't actually contain any information? I have tried using 'drop.unused.levels=TRUE', but there doesn't seem to be any effect. Here is an example: library(lattice) # some fake data: d <- data.frame(x=runif(20), x.class=rep(letters[1:5], each=4), f1=rep(letters[1:2], each=10), f2=rep(letters[10:19], each=2) ) # plot

Hi, I am curious about how to interpret the results of a polynomial regression-- using poly(raw=TRUE) vs. poly(raw=FALSE). set.seed(123456) x <- rnorm(100) y <- jitter(1*x + 2*x^2 + 3*x^3 , 250) plot(y ~ x) l.poly <- lm(y ~ poly(x, 3)) l.poly.raw <- lm(y ~ poly(x, 3, raw=TRUE)) s <- seq(-3, 3, by=0.1) lines(s, predict(l.poly, data.frame(x=s)), col=1) lines(s,

Hi, How would one go about determining if the slope terms from an analysis of covariance model are different from eachother? Based on the example from MASS: library(MASS) # parallel slope model l.para <- lm(Temp ~ Gas + Insul, data=whiteside) # multiple slope model l.mult <- lm(Temp ~ Insul/Gas -1, data=whiteside) # compare nested models: anova(l.para, l.mult) Analysis of Variance

Hi, Running the following example from ?Predict() throws an error I have never seen before: set.seed(1) x1 <- runif(300) x2 <- runif(300) ddist <- datadist(x1,x2); options(datadist='ddist') y <- exp(x1+ x2 - 1 + rnorm(300)) f <- ols(log(y) ~ pol(x1,2) + x2) p1 <- Predict(f, x1=., conf.type='mean') Error in paste(nmc[i], "=", if (is.numeric(x))

Good Morning, I am trying to get side by side boxplots of two groups on the same variable. The last item under ?boxplot led me to some useful code. I use "boxwex" to make the boxes narrower, "at" to shift them over and "add" to draw them both on the same graph. Something along the lines of: attach(group1) boxplot(Y~X, col="blue", boxwex=.4,