similar to: calculate spatial distance

Hei, I have two spatial datasets Sa and Sb, both with lat-lon coordinates and from same geographic area, but from different localities within the area (independent samples). Sa is biotoc data, Sb is some environmental parameter (fertility). I 'know' that Sb affects Sa, but wonder on which scale. I tried different interpolations by creating different grids of Sb (e.g. 20x20 and 100x100

Hi group, I have this type of data x(predictor), y(response), factor (grouping x into many groups, with 6-20 obs/group) I want to fit a linear regression with one common intercept. 'factor' should only modify the slopes, not the intercept. The intercept is expected to be >0. If I use y~ x + factor, I get a different intercept for each factor level, but one slope only if I use y~ x *

Hei Group, I want to compare the relative importance of predictors in a multiple linear regression y~a+bx1+cx2... However, bptest indicates heteroskedasticity of my model. I therefore perform a robust regression (rlm), in combination with bootstrapping (as outlined in J. Fox, Bootstrapping Regression Models). Now I want to compare the relative importance of my predictors. Can I rely on the

Dear Listers, I have a regression problem (x->y) with biological data, where x influences y in two ways, (1) y increases with x and (2) the variation around the mean (residuals) decreases with increasing x, i.e. y becomes more 'predictable' as x increases. The relationship is saturating, y~a + bx + cx^2, gives a very good fit. I know basically how to test for heteroscedasticity. My

Dear, I am trying to visualise a time-progressing line (it's supposed to represent spread patterns) using brew package and Google Earth. The idea is to have a function which takes start and end point geographic coordinates, as well as number of intervals to chop the path up, and returns the collection of points segmenting this line. Unfortunately my calculations fail for large distances,

Dear R users, I need to find the coordinates for the point (midpoint) located half way between two pairs of coordinates (lon1,lat1 and lon2,lat2) assuming a straight line between them. What would be the best way? I tried to find an answer in the help archives but without success. I would greatly appreciate any help. df<- data.frame(lon1=c(-4.568,-4.3980), lat1=c(59.235,56.369),

I am wondering if there is a function which will do a join between 2 data.frames by minimum distance, as it is done in ArcGIS for example. For people who are not familiar with ArcGIS here it is an explanation: Suppose you have a data.frame with x, y, coordinates called track, and a second data frame with different x, y coordinates and some other attributes called classif. The track data.frame has

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues Is there a function to calculate distances between adjacent latitude/ longitude pairs in a matrix? It is basically a spatial diff() function that I have in mind. Data: long1, lat1 long2, lat2 long3, lat3 looking for: diff(data$long, data$lat)

All - I have a large data frame that looks like ID p1 p2 p3...p20 Lat1 Lat2 Lat3...Lat20 Long1 Long2 Long3...Long20 1 0 0 1 0 NA NA 29.xx NA NA NA -89.xx NA 2 1 0 0 1 27.xx NA NA 29.00 -88.00 NA NA -89.xx 3 0 0 0 0 NA

Deemed colleagues I would appreciate your help with a sentence to calculate the linear distance between 2 geographical points (coordinates in UTM). In advance thnks for your attention, -- Ricardo Bandin Llanos rbandin@udec.cl Estudiante - Magíster Cs. m. Pesquerías Universidad de Concepción, Región del Bio-Bio, Chile Celular: (0056-41) 97949957 [[alternative HTML version deleted]]

Dear R-listers Is there anyone who knows why I get different eigenvectors when I run MatLab and R? I run both programs in Windows Me. Can I make R to produce the same vectors as MatLab? #R Matrix PA9900<-c(11/24 ,10/53 ,0/1 ,0/1 ,29/43 ,1/24 ,27/53 ,0/1 ,0/1 ,13/43 ,14/24 ,178/53 ,146/244 ,17/23 ,15/43 ,2/24 ,4/53 ,0/1 ,2/23 ,2/43 ,4/24 ,58/53 ,26/244 ,0/1 ,5/43) #R-syntax

Hello, This is what I am trying to do: I wrote a little function that takes addresses (coordinates) as input, and returns the road distance between every two points using Google Maps. Catch is, there are 2000 addresses, so I have to get around 2x10^6 addresses. On my first go, this is what I did: ######################################### getRoadDist = function(X,complete=F){ # X must be a

Hi lily, It's not too hard to do it using dataframes. Getting the indexing right is usually that hardest part: # these values are the centers of the black cells lat<-rep(28:38,11) lon<-rep(98:108,each=11) pop<-sample(80:200,121) # just use the data.frame function blackcells<-data.frame(lat=lat,lon=lon,pop=pop) plot(0,type="n",xlim=c(97.5,108.5),ylim=c(27.5,38.5),

Hello, I am trying to match lat/lon from one dataset with the lat/lon from a second dataset and use that rows data for calculations. I am using match, but this is finding the first match and not comparing the pair, how can I determine if the lat/lon are the same? See example below. Is there a better way to determine to a matching pair of lat/lon values? Example Datasets: > data2

Hi Jim, Thanks. It works. I now have more complex problems. If at each blackcell, there are two variables such as pop and mood. For each variable, there are daily records in one year, so 365 records for pop and 365 records for mood. The averaged values for the redcells should be daily records too. What kind of format do you recommend for this problem? Right now, I just get the latitudes and

Dear R-listers I wonder if someone can help me with the syntax for the random effect in glmmPQL()? I have a data set with a response variable "y" (counts), two dependent variables: "treat" (4 levels) and "site" (2 levels). The latter, I want to use as a random variable. How do I specify this in the function? Is it like this:

dear listers, I use gam (from mgcv) for evaluation of shape and strength of relationships between a response variable and several predictors. How can I interpret the 'F' values viven in the GAM summary? Is it appropriate to treat them in a similar manner as the T-statistics in a linear model, i.e. larger values mean that this variable has a stronger impact than a variable with smaller F?

Hi all! I have a problem setting ACLs on a remote file on a Windows XP Pro SP2 box. I issue the following command: smbcacls -a 'ACL:BBI-DEV\beakid:ALLOWED/0/0x00100116' -U 'BBI-DEV \Admin' //BBI-DEV/Data /Niva.txt And I get this response from debug level 3. Password: Connecting to host=BBI-DEV Connecting to 192.168.1.124 at port 445 Doing spnego session setup (blob

Hi all! I have a problem setting ACLs on a remote file on a Windows XP Pro SP2 box. I issue the following command: smbcacls -a 'ACL:BBI-DEV\beakid:ALLOWED/0/0x00100116' -U 'BBI-DEV \Admin' //BBI-DEV/Data /Niva.txt And I get this response from debug level 3. Password: Connecting to host=BBI-DEV Connecting to 192.168.1.124 at port 445 Doing spnego session setup (blob

Dear R-listers I'm a new R-user who needs some help with a test that I want to do. I have done a field experiment: four treatments (cont, x, y and xy) at three sites (A, B and C), the response is count data (0 - 15). I've done a Poisson regression: >glm(response~as.factor(treatment)*as.factor(site), family=quasipoisson, offset(max.response), data=dat) The "offset" is the