search for: variog

Hi, I'm a new R user. My goal is to do a variogram using geoR. I started by trying to do the example in the geoR Illustrative Session using my own data. I am able to read in my Ascii data using: D <- matrix(scan("file.dat", n=530*3), 530,3, byrow=TRUE). Then I use: as.geodata(D, coords.col=1:2, data.col=3) to make the object D...

I have what R seems to consider a very large dataset, a 12MB text file of lat,long,and height values, 130,000 rows to be exact. Here's what I get: Thomas Colson North Carolina State University Department of Forestry and Environmental Resources (919) 673 8023 tom_colson at ncsu.edu Calendar: www4.ncsu.edu/~tpcolson

I'm using R for Mac OSX version 1.14 (2129) and the geoR package version 1.6-5 (the current version in the R repository). I'm running R in OS 10.4.6 on a Mac G4 iBook (933MHz, 640 MB DDR SDRAM). I searched the R archive and did not find a posting on this issue. I want to use the variog and variog4 functions of geoR to characterize the pattern of spatial autocorrelation of tree density on a forest plot. But I get incomplete line plots when I plot the output of variog4, compared to the plot for the output of variog. I'm using the same geodata for each plot. I've at...

Hello, I am attempting to get the standard deviation in multiple distance bins in my spatial data. It appears as though the 'variog' command in the geoR package will do the trick, as one of the outputs from 'variog' is 'variog$sd', which, according to the manual, is the "standard deviation of the values in each bin". However, when I run this command, the standard deviation values are much lar...

Dear GeoR-er, If I use the variog function in the latest release of geoR, the first lag is always ignored. For instance, if you read in geodata, calculates the variogram using the variog function and give in a uvec like uvec=seq(0,max,by=2.44), it only starts giving results from distance=4.88 and ignores 2.44! This wasn't the c...

dear list I am student M.S. statistics in department statistics . I am working in the function "nls" in the [R 2.3.1] with 246 data and want to fit the "exp" model to vectors( v and u ) but I have a problem to use it u 5.000000e-13 2.179057e+03 6.537171e+03 1.089529e+04 1.525340e+04 1.961151e+04 2.396963e+04 2.832774e+04 3.268586e+04 3.704397e+04 4.140209e+04

...min 1.233673 15.82129 #max 8.464283 34.30390 # #Distance summary # min max # 0.2962488 19.5670141 # #Data summary # Min. 1st Qu. Median Mean 3rd Qu. Max. # 296.1 336.3 345.5 351.9 366.5 422.1 plot(w1.geo) # so far so good plot(w1.geo,lambda=0.1) #ditto w1.geo.vc<-variog(w1.geo,option="cloud",max.dist=summary(w1.geo)$distances.summary[2],lambda=lambda) #variog: computing omnidirectional variogram plot(w1.geo.vc) w1.geo.lf<-likfit(w1.geo,cov.model="matern",ini.cov.pars=c(2,0.03),kappa=1,fix.kappa=FALSE,nugget=0.01,lambda=lambda,fix.lambda=FALS...

...y test one period data################## ptemp <- ppt1[,3] ll <- which(ptemp>0) ppt2 <- matrix(0,nrow=length(ll),ncol=3) # (lon,lat,ptemp) ppt2[,1] <- lat[ll] # y-axis ppt2[,2] <- lon[ll] # x-axis ppt2[,3] <- ptemp[ll] # ppt pptd <- as.geodata(ppt2) bin1 <- variog(pptd) # plot(bin1) # fig1 bin2 <- variog(pptd,estimator.type="modulus")# plot(bin2) # fig2 ini1 <- max(bin1$v) ols <- variofit(bin1, fix.nugget = F,weights="cressie",ini.cov.pars=c(ini1,4)) kc <- krige.conv(pptd, loc=pgrid,krige=krige.control(type.krige=&q...

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...the basic idea is to implement a binary partitioning algorithm to determine the optimal cutpoint based on deviance measures obtained from likelihood estiamtes. This is in the geo-spatial context so I'm actually using the geoRglm package to obtain this likelihood fit. I initially use the "variog" function to help specify the initial parameter values passed to "likfit" to ensure convergence. Although not the most elegant solution, the code works ... I just want to re-code it to avoid using the "for" loop. Any help would be greatly appreciated. This is what I'...

Please see the code below. When I try to run the variogram - vg.deft<-variog(rd,uvec=10) I keep getting this error- variog: computing omnidirectional variogram Error in vector("double", length) : vector size specified is too large Also, when I try to define distance-based neighborhood - nb.tr=dist.neighbors(tr.locs,2) I get this error - Er...

Hi all, I tried to produce some kriged surfaces with geoR (latest version). The size of the grid should be around 900 x 650 cells (what I find is not a very big grid), and the number of points is around 2500. The command krige.conv stopped after arround 5 min saying it can not allocate a vector with around 1.5 billion units. Sounds reasonable. Is there a workaround? How would I partition the

I wonder what is the default value for the argument 'cutoff' when not specified in the variogram.formula function of gstat. Computing variogram envelops within gstat, I am comparing the results obtained with variog in geoR and variogram in gstat, and it took me a while before understanding that the cutoff default value is not the maximum distance. Can Edzer tell us about it? All the b...

Hello All! I calculate a variogram using the function variog (package geoR) afterwards I use variofit to fit a spherical model (see code below). Now I just changed the units of the variable (in this case MPa to kPa just a factor of 1000). If I do so, I get a different fit and therefore different ranges etc. Why? The semi-...

...te the distance matrix yourself from the coordinates file (but you may meet meory problem anyway). Still more straigthfully, if you intend to use interpolation methods such as kriging, you don't need to manage the distance matrix building by yourself. See: library(geoR) library(help=geoR) ?variog ?variofit ?likfit? etc... If you want further use geostatics (eg via geoR or gstat), you will anyway have to manage with memory limits (not due to R). On my computer (portable HP compaq nx7000) I can hardly manage with more than 2000 observations using geoR (far from your 18227 observations)....

...age: age of death (22 27 32 37 42 47 52 57 62 67 72 77 82) year: year of death (1980:2002) I don?t have problem to fit the model, but in residual analysis I have one problem. If i type acf(m1.lme$residuals) the graph show 4 plot with a sin curve (a example in attach) and I get this variogram: > Variogram(m1.lme) variog dist n.pairs 1 0.3939065 1 276 2 0.6486452 2 253 3 0.9679870 3 230 4 1.2765094 4 207 5 1.4158147 5 184 6 1.4264685 6 161 7 1.4048608 7 138 8 1.1902613 8 115 9 0.9619330 9 92 10 0.7037...

All, I am new to using R and know some basics. I wish to use kriging in R to do the following: given data Y =f(X1,X2,X3,.....,Xn) --1000+ irregular measured data set. I would like to be able to get a single value y given sinle input set (x1,x2,x3,...xn) A google search on this takes me lierally to the same example on involving analysis with soil sampling and I cannot figure out how to

I'm a PhD student and I'm working with covariance function. I'm interested to know if exist some packages in R to calculate and plot the bidimensional Autocovariance Function. the input matrix is a matrix that describe a spatial location over a 2-D space and I want to use it in the same way I can use a time serie in the 1-D acf. Thanks, Nicola.

I'm a PhD student and I'm working with covariance function. I'm interested to know if exist some packages in R to calculate and plot the bidimensional Autocovariance Function. the input matrix is a matrix that describe a spatial location over a 2-D space and I want to use it in the same way I can use a time serie in the 1-D acf. Thanks, Nicola.

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