similar to: estimate phase shift between two signals

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

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

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, 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

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Hi, is there a function in R to convert data read with read.shape and which is originally in UTM coordinates into longitude / latitude coordinates? I found the convUL() function from the PBSmapping package but I have no idea how I could apply that to the read.shape object. Many thanks, Werner __________________________________________________ Do sragenden Schutz gegen Massenmails.

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

Hello: I would like to superimpose vector polygons (state outlines) from a Shape file on top of a satellite image, imported into a SpatialGridDataFrame from GEOTIFF via gdal_translate and readGDAL. When I plot polygon and point shape files in R, into SpatialPointDataFrame and SpatialPolygonDataFrame, the two feature sets line up geographically, so it seems logical that a SpatialGridDataFrame

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

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))

Hi, I recently upgraded to R 2.9.0 on linux x86. After doing so, I switched to the RPostgreSQL package for interfacing with a postgresql database. I am using postgresql 8.3.7. A query that works from the postgresql terminal is causing a segfault when executed from R. My sessionInfo, the error message, and the R code used to generate the error are listed below. I have noticed that a

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 All, I'm trying to automate a data summary using summary or describe from the HMisc package. I want to stratify my data set by patient_type. I was hoping to do something like: Describe(myDataFrame ~ patient_type) I can create data subsets and run the describe function one at a time, but there's got to be a better way. Any suggestions? Rachel [[alternative HTML

I would like to use a map or aerial photo as a background to plotting solid lines and text, and semi-transparent color contours, in base and lattice graphics. Plot coordinates need to be consistent with the georeferenced background. For example, a color contour plot would have an gray-toned aerial photograph as a background for overprinted semi-transparent color contours of some spatially

Greetings, I am a bit confused by the results returned by the functions: cohen.kappa {concord} classAgreement {e1071} when using a two-way table. for example, if I have an matrix A, and a similar matrix B (same dimensions), then: matrix A and B can be found: http://casoilresource.lawr.ucdavis.edu/drupal/files/a_40.txt http://casoilresource.lawr.ucdavis.edu/drupal/files/b_40.txt A <-

Hi, is it possible to reverse the order in which panel.lmline() or panel.smooth() operation in xyplot() ? This type of situation might occur when plotting some variable with depth, but the relation we want to describe is variable ~ depth, and not depth ~ variable, as the plotting formula would suggest. # an example: d <- 1:100 v <- d * rnorm(100) xyplot(d ~ v, ylim=c(100,0),

Hi, I was recently splitting some massive phylo class objects with extract.clade() and noticed what appears to be a bug in how tip labels are copied from the full tree to the pruned tree. This possible bug was also mentioned here: http://www.mail-archive.com/r-sig-phylo at r-project.org/msg00537.html An example: library(ape) set.seed(5) x <- matrix(rnorm(100), ncol=10) p <-