

 Dear Roger, 

I tried with data frames instead of SPDF. I gave some details of names and class types of datasets. Grid data has 31204 rows (first row is column names) and 5 columns (Z,X,Y,V1,V2). Station data has 226 rows (first row is column names) and 6 columns (PREC,Z,X,Y,V1,V2). I gave an example about datasets below. 

Grid data
Z   X   Y   V1  V2
495 259725.32564500000 5010656.22353999000 44.15584946 53525.25605680000
621 264725.32564499800 5010656.22353999000 50.67575455 50139.84515760000
432 274725.32564499800 5010656.22353999000 58.62472534 44295.66734330000
418 279725.32564499800 5010656.22353999000 45.05175400 41966.14328090000
361 254725.32564500000 5005656.22353999000 37.61386871 60596.18505359990

Station data
PREC  Z X   Y   V1  V2
514.3522848 1039 410428.05168500000 4478786.07400999000 100.69618225 81321.18533050000
650.6115948 29 942127.25593400000 4409537.10120000000 7.64556551 34796.24442280000
690.1826088 614 1201166.68404000000 4496907.09750000000 39.14785004 212666.95252600000
427.7718516 1213 1080214.69930000000 4550293.99677000000 53.82775879 164788.61213900000
402.9552240 1197 525196.23761299900 4619486.48904000000 69.23021698 206901.35695100000

And from the list Binbin lu send me a message, according to his advice I don't write "station$" term while performing gwr.sel and gwr functions. In this way gwr function has worked but gave a warning message. And when I plot the predicted precipitation values of the grid there are some negative values which should't be occur! It didn't calculate predicted errors also.

What do you mean with 'factor' and I don't know how to run the function under debug. 

Thanks for your help.
Pinar

###########################################################################
> grid<-read.table("D:\\R\\dem.txt", header=TRUE)
> station<-read.table("D:\\R\\station.txt", header=TRUE)

> class(grid)
[1] "data.frame"

> class(station)
[1] "data.frame"

> names(grid)
[1] "Z"  "X"  "Y"  "V1" "V2"

> names(station)
[1] "PREC" "Z"    "X"    "Y"    "V1"   "V2"  

> coordinates(station) <- c("X", "Y")
> coordinates(grid) <- c("X", "Y")

> bw=gwr.sel(PREC~Z+V1+V2,data=station,adapt=T)
> gwr <-gwr(PREC~Z+V1+V2,data=station,adapt=bw, fit.points = grid, predict=T, se.fit=T, hatmatrix=T)

Warning message:
In gwr(PREC ~ Z + V1 + V2, data = station, adapt = bw, fit.points = grid,  :
  standard errors set to NA, normalised RSS not available

Alinti Roger Bivand <Roger.Bivand@nhh.no>

> On Fri, 11 Jun 2010, Pinar Aslantas Bostan wrote:
>
>>
>>
>> Dear all,
>>
>> I want to make GWR analysis to predict precipitation distribution 
>> measured from 225 meteorological stations. I have three independent 
>> variables (Z, V1, V2). I want to obtain predictions on the grid 
>> dataset which has 31203 number of pixels. I gave some details about 
>> my datasets below. While performing GWR, I get error message: "new 
>> data matrix rows mismatch"
>>
>> How can I solve that problem?
>
> You need to provide the detailed output of traceback(), and probably 
> also run gwr() under debug() to see whether this is a data problem or 
> a code problem. Does gwr() work when predict=FALSE, and/or 
> predict=TRUE, se.fit=FALSE? The error message is generated when the 
> number of columns in the matrix of X variables is not the same in 
> data and and fit.points. Are the variables in both cases stored in 
> the same way? What do str(station.grid) and str(station) look like 
> before conversion to SPDF and after? Is one variable a factor in one 
> and numeric in the other? Running under debug() will let you check 
> what x and predx look like.
>
> If this sounds hard, consider putting your data on a website and 
> posting the link.
>
> Hope this helps,
>
> Roger
>
>>
>> Thanks, Pinar.
>>
>> station.grid<-read.table("D:\\R\\dem.txt", header=TRUE)
>> station<-read.table("D:\\R\\station.txt", header=TRUE)
>>
>> grid = SpatialPointsDataFrame(data=station.grid, 
>> coords=cbind(station.grid$X, station.grid$Y))
>
>> station = SpatialPointsDataFrame(data=station, 
>> coords=cbind(station$X,station$Y))
>>
>>> names(grid)
>> [1] "Z" "X" "Y" "V1" "V2"
>>> names(station)
>> [1] "PREC" "Z" "X" "Y" "V1" "V2"
>>
>> bw=gwr.sel(PREC~station$Z+station$V1+station$V2,data=station,adapt=T)
>
>> gwr <-gwr(PREC ~ station$Z +
> station$V1 + station$V2, data=station, adapt=bw, fit.points = grid, 
> predict=TRUE, se.fit=T)
>>
>> Error in gwr(PREC ~ station$Z + station$V1 + station$V2, data = station, :
>> NEW DATA MATRiX ROWS MiSMATCH
>>
>> ----------------------------------------------------------------
>>
>>
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>>
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>>
>
> -- 
> Roger Bivand
> Economic Geography Section, Department of Economics, Norwegian School of
> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
> e-mail: Roger.Bivand@nhh.no
>
>



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