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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 <- matrix(unlist( read.table('a_40.txt'), use.names=FALSE), ncol=14) B <- matrix(unlist( read.table('b_40.txt'), use.names=FALSE), ncol=14) # compute cohen's kappa, def...

...(sample(x$y, 100)) } mean(m) } system.time(ddply(d, .(id), .fun=f, .parallel=FALSE)) # user system elapsed # 2.740 0.016 2.766 system.time(ddply(d, .(id), .fun=f, .parallel=TRUE)) # user system elapsed # 2.720 0.000 2.726 -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

...rpreting the use or output from spectrum() here? If so, is there a general procedure for estimating a phase-shift between two noisy signals? Would I first have to fit a smooth function in order to solve this analytically? Thanks in advance, -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

...les=list(draw=T), xlab="Easting (m)", ylab="Northing (m)") ... seems to work well. However the polygon boundaries are colored black. If possible I would like the boundaries to not be drawn at all. any tips? cheers, Dylan -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

...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 -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

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 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

...s.vector(coef(l.poly.raw)) -0.1025114 1.5265248 2.0617970 2.7393995 When using continuous data in both Y and X, does the difference between "raw" and "orthagonal" polynomials have any practical meaning? Thanks, Dylan -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

...into whether or not the two slope terms (InsulBefore:Gas and InsulAfter:Gas) were different. However, is there a formal test for this sort of question, and can it be generalized to differences between more than 2 slope terms? Thanks, Dylan -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

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...lyr_0.1.9 mgcv_1.5-5 RColorBrewer_1.0-2 nlme_3.1-94 [5] rms_2.1-0 Hmisc_3.7-0 survival_2.35-6 lattice_0.17-25 loaded via a namespace (and not attached): [1] cluster_1.12.0 Any ideas? Thanks! Dylan -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

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

...rcs(x)] ~ z. Is this interpretation of RCS coefficients even possible? If not, would forcing knot locations make it a possibility? Or, would modeling both knots and RCS coefs with external variables lead to sensible predictions? Cheers, Dylan -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

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...=0.5), se='ker') # without weights # note error message summary(rq(sand ~ method, data=x, tau=0.5), se='ker') # without weights, no error message summary(rq(sand ~ method, data=x, tau=0.5, method='fn'), se='ker') -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

...e packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] RPostgreSQL_0.1-4 DBI_0.2-4 ---------------------------------------------------------------------------------------------------- -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

...ation of Cohen's Kappa (using the cohen.kappa function from the 'concord' package) : # a and b are vectors with the 'factor-ized' matrices, stored as vectors cohen.kappa(table(a,b), type='count') A lengthy summary of this small adventure has been recorded here: http://casoilresource.lawr.ucdavis.edu/drupal/node/275/ Please note that I am looking for a *better?* way to compare these two matrices. It could be that the Cohen's Kappa, and difference maps are the best that I am going to get. Thanks in advance, -- Dylan Beaudette Soils and Biogeochemistry Graduate Group...

hello, I have this simple question. This is my dataset size 1 57 2 97 3 105 4 123 5 136 6 153 7 173 8 180 9 193 10 202 11 213 12 219 13 224 14 224 15 248 16 367 17 496 18 568 19 618 20 670 21 719 22 774 23 810 24 814 25 823 I plot it with: plot(generalstats[,1], type="b", xlab="Mesi", ylab="Numero di vertici", main=""); and try to interpolate with a

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