similar to: Saving iterative components

Hi all I am trying to run samba-3.0.28 on a solaris 10 sparc machine, as a member server for an AD 2003R2. I use nss_ldap-254. I compile samba with: GCC_EXEC_PREFIX=/opt/csw/gnu/ LDFLAGS="-L/opt/csw/lib" CPPFLAGS="-I/opt/csw/include" ./configure --prefix=/opt/samba --with-acl-support --with-quotas --with-included-popt --with-privatedir=/opt/samba/etc/samba/private

Hello again, There is any package which does Z aware (real 3D) interpolations? It can be any method (IDW, kriging or spline) but it should take into consideration not only x and y coordinates for interpolation, but also z coordinate. I looked into different packages but it seems i didn't find the right one. The ultimate goal is to import the output into a GIS (Geographical Information

Emilio, muchas gracias. Tuve que rehacer el código para entender mejor todo, pero me sale el siguiente error: *Error in as.data.frame.default(x[[i]], optional = TRUE) : cannot coerce class ?structure("RasterLayer", package = "raster")? to a data.frame* El código es el siguiente: *for (i in 1:nrows_mt) { data_it_mt <-

Hi everybody: I just generate interpolation maps with differents methods, like IDW and kriging, and now i want to compare the predict values versus real, and i don't who is the commant to do it. I want for example, if I pass from console the coordinates of a place, return me the predict value. Could anybody tell me how should do?. Thanks in advance --

hi all, I have a plot to which i would like to add text labels. And i cant find a way...here is the code : enaD2<-idw(D2~1, loca=dva, newdata=grd) pts = list("sp.points", dva, pch = 20, cex=1.5, col = "darkred spplot(enaD2, "var1.pred",sp.layout=pts, main = "globina 60 cm", sub="D2",

Hi everybody: Could anybody help how I solve the next problem?. I'm doing interpolation maps of tropospheric ozone of my region, and after create it using IDW, and kriging methods, I want from shapefiles (*.shx, *.shp, *.dbf, *.sbx & *.sbn ) create contour over the interpolation maps. Could anybody tell me how do it?. Thanks in advance. ###################################### Antonio

Hi everybody: I just generate different maps of interpolation with different methods but with the same package -(gstat, i used the krige command). And now for evaluate the best method i want to compare the predict values versus experimental, but i don't know how do it. Could anybody tell me how should do it?. Thanks in advance. -- ######################################## Antoni Vi??dez

Now I have the forest plot data with x, y locations, and I measured the DBH for every indivicuals. The data looks like that: x=runif(100,0,100) y=runif(100,0,100) dbh=runif(100,1,100) rdata=data.frame(x,y,dbh) > rdata[1:5,] x y dbh 1 99.5354145 1.412844 34.10112 2 0.8259361 87.737036 39.12914 3 6.5678613 65.699032 22.55990 4 67.2987881 72.053877 45.83978 5 2.2491372

Hello, Apologies if this is the wrong list, I am a first-time poster here. I have an experiment in which an output is measured in response to 42 different categories. I am only interested which of the categories is significantly different from a reference category. Here is the summary of the results: summary(simple.fit) Call: lm(formula = as.numeric(as.vector(TNFa)) ~ Mutant.ID, data =

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Hola, buen día a todos. He estado mirando cómo interpolar unos datos anuales con el método IDW, pero no consigo aún realizarlo. idw_models <- list() for (i in 1:ncol(data_y_mt)) { #Extract the current variable current_var <- names(data_y_mt)[i] #Create an IDW model for the current variable idw_model <- idw(current_var, sta_mt, grid, p = 1) idw_models[[i]] <- idw_model }

Hi, I have a question on testing spatial autocorrelation on raster data including NA-values. In particular, I like to calculate Moran?s I and Geary?s C indices by using inverse distance weighting matrices. Calculating Moran?s I with moran.test works fine, because the function contains the option "na.action=na.pass". Unfortunately, the function geary.test does not contain this

Hello all, I want to interpolate some data i prepared in GRASS, so I'm looking for what interpolation methods are available for R. In GRASS I can do Splines with tension and IDW. I'm looking for something like multiquadric equations. Is there any function/package available fo rthis? thanks all -- +-------------------------------------------------+ Carlos Henrique Grohmann de

Soon on CRAN a new version of package gstat will emerge, which has a few minor changes and possible incompatibilities w.r.t. the previous version(s). The new gstat (0.9-23) now: + depends on sp, and uses internally with Spatial* classes from sp if data are provided in the old-fashoned way (as data.frame) + has a vignette to get you started with the classes in sp + defines krige as a generic;

Soon on CRAN a new version of package gstat will emerge, which has a few minor changes and possible incompatibilities w.r.t. the previous version(s). The new gstat (0.9-23) now: + depends on sp, and uses internally with Spatial* classes from sp if data are provided in the old-fashoned way (as data.frame) + has a vignette to get you started with the classes in sp + defines krige as a generic;

Hello, I have a question on sp package. I drew pixel heat maps of continental U.S. using insurance litigation data. If an insurance claim is litigated at a certain location, 1 is assigned; otherwise 0 is assigned. I have assigned a value between 0 and 1 to each pixel on my map using inverse-distance weighting (spatial smoothing). I need to draw two pixel maps, one for period 2001-2006 and the

Hi All, I've gotten a number of reports from users about gplots::heatmap.2 generating 'node stack overflow' errors. As it turns out, these errors originate in stats:::plotNode, and are triggered when it is passed a dendrogram that is too deeply nested. While increasing the stack size (which is a compile-time option for byte coded functions) can allow a particular instance to

Hi, We have some sample data from the US census, and we know the marginal totals for the population. We need to make the population estimates add up to the correct sums. I have two questions: Is there some package in R which does this adjustment, by any means? Is there some more modern reference for this problem than Deming's 1943 monograph, ``Statistical Adjustment of Data''?

Dear all, I wonder if there are some function or package in R which can do the iterative proportional fitting. In the exponential model f(y1,...yn)=exp(a'yi+b'(yi*yj)+.....+c'(y1*...*yn)+constance), instead of the canonical parameters, I use maginal probability instead of a and log odds ratio instead of b. and for the order higher than 3, I use the canonical way or even assume

I've been asked, and interested myself: Has anybody implemented the above in R or another S language dialect? We are talking about the algorithms / methodology by Wellner, Groeneboom and Jongbloed, e.g., from the following article @Article{Jongbloed:1998:ICM, author = "Geurt Jongbloed", title = "The Iterative Convex Minorant Algorithm for