similar to: Access to particular predict value

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

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

Hello everyone, When looking for information about clustering of spatial data in R I was directed towards DBSCAN. I've read some docs about it and theb new questions have arisen. DBSCAN requires some parameters, one of them is "distance". As my data are three dimensional, longitude, latitude and temperature, which "distance" should I use? which dimension is related to

Hi everyone As I couldn't succeed with manual installation of Rmpi I decided to start again from the beginning. I removed R and MPICH in my Ubuntu Hardy installation. Then, to avoid any dependencies problems I have installed MPICH and R from synaptic, not from sources. But now I can't install Rmpi. An error message appears when trying to install Rmpi, you can find in

Hi R-users I'm a beginner with R and statistics, so I need some help to start my data analysis. I've been reading some docs and tutorials on R and cluster analysis. I've got a large dataset (102000 points) with values of longitude, latitude and temperature and want to see if I can find groups (clusters). Following some tutorials I can look for principal components but get an error

Hi everyone I am new to R and have a question about missing values. I am trying to do a cluster analysis of monthly temperatures and my data are 14 columns with spatial coordinates (lat,lon) and 12 monthly values: /lat - lon - temp1 - //temp2 - temp3 - .... - //temp12/ If I omit missing values (my missing values are 99.00) with /mydata <- na.omit(mydata)/ every row with a

Hi everyone I want to install Rmpi to use R in parallel mode in a Linux cluster (Ubuntu, Hardy Heron). It seems to be properly installed but a problem appears when loading Rmpi library. R version 2.11.1 (2010-05-31) > library("Rmpi") Error: package 'Rmpi' was built before R 2.10.0: please re-install it Should I remove R-2.11 and install R-2.10? I have tried to

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

Hi, I need help! I am trying to iterate an iterative process to do cross vadation and store the results each time. I have a Spatial data.frame, called Tmese > str(Tmese) Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots ..@ data :'data.frame': 14 obs. of 17 variables: .. ..$ ID : int [1:14] 73 68 49 62 51 79 69 77 57 53 ... .. ..$

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 <-

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

Tengo dos dataframe que corresponden a los valores horarios de los contaminantes y el otro a los valores horarios de las variables meteorológicas para el mismo periodo de tiempo. La variable temporal date en ambos dataframe tiene el formato dmy_hms. Los dataframe tienen diferente número de filas. dataframe contaminantes contiene 175247 filas y el dataframe meteorología 175321. Quiero saber

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",

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

Dear R-users, I'm sure it must be a specific function or a better way to convert matrix to x,y,z coordinates (and viceversa), than my function below (it works). Any help? m2coord <- function(m) { k <- nrow(m)*ncol(m) aa <- data.frame(r=1:k, c=1:k, v=1:k) k <- 0 for (i in 1:nrow(m)) for (j in 1:ncol(m)) { k <- k+1 aa$f[k]=i; aa$c[k]=j; aa$v[k]=m[i,j] } aa } Juli

Dear colleges, I'm trying to combine a barplot and a plot in a single figure as follows: data <- 1:6 t <- barplot(data, axes=F) par(new= T) plot(t, data, type="b") However, as you can see in the example, the dots of the second plot do not fall in the midpoint of the bars in the first. Any trick for setting the 2 plots at the same scale? I have unsuccessfully tried: plot(t,

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 =

I don't quite understand the difference between the two methods for performing a chi-squared test on contingency tables: summary(table()) and chisq.test() They may different results. E.g.: aa <- gl(2, 10) bb <- as.factor(c(1,2,2,2,1,2,1,2,2,2,1,2,2,2,1,1,1,2,1,1)) aa <- c(aa, aa) bb <- c(bb, bb) table(aa, bb) summary(table(aa, bb)) chisq.test(aa, bb) Could somebody give me

Hi, Thanks for showing me how to use RODBC and odbcConnect. Now works nicely. The question I've got now is: noms <- list.files(pattern=".DBF") # removing extension names: noms <- sapply(noms, function(x) as.character(strsplit(x,".DBF")) , USE.NAMES=F) for (i in 1:length(noms)) { s <- sqlFetch(bdades, noms[i]) # etc. } But it seems that sqlFetch()