generating object with multiple polygons

Dear all,

This might be a newbie question, so I'd appreciate your patience with this.

I'm obtaining climatic data from worldclim and generating polygons based on
different climatic limits:

library(raster)
xx<-getData('worldclim', var='bio', res=10)$bio1
slice1 <- rasterToPolygons(xx, fun = function(x) {x > 200 & x < 260})
slice2 <- rasterToPolygons(xx, fun = function(x) {x > 250 & x < 300})

Now, I'd like to combine "slice1" and "slice2" into the same
"SpatialPolygonsDataFrame" object, but I do not want to merge them.

Any help will be greatly appreciated.

Karla

        [[alternative HTML version deleted]]

Dear all,

This might be a newbie question, so I'd appreciate your patience with this.

I'm obtaining climatic data from worldclim and generating polygons based on
different climatic limits:

library(raster)
xx<-getData('worldclim', var='bio', res=10)$bio1
slice1 <- rasterToPolygons(xx, fun = function(x) {x > 200 & x < 260})
slice2 <- rasterToPolygons(xx, fun = function(x) {x > 250 & x < 300})

Now, I'd like to combine "slice1" and "slice2" into the same
"SpatialPolygonsDataFrame" object, but I do not want to merge them.

Any help will be greatly appreciated.

Karla

        [[alternative HTML version deleted]]

Karla,
You can do

library(raster)
slices <- bind(slice1, slice2)

Robert

On Sun, Apr 3, 2016 at 6:53 AM, Karla Shikev <karlashikev at gmail.com>
wrote:

Dear all,

This might be a newbie question, so I'd appreciate your patience with

this.

I'm obtaining climatic data from worldclim and generating polygons based

on

different climatic limits:

library(raster)
xx<-getData('worldclim', var='bio', res=10)$bio1
slice1 <- rasterToPolygons(xx, fun = function(x) {x > 200 & x < 260})
slice2 <- rasterToPolygons(xx, fun = function(x) {x > 250 & x < 300})

Now, I'd like to combine "slice1" and "slice2" into the same
"SpatialPolygonsDataFrame" object, but I do not want to merge them.

Any help will be greatly appreciated.

Karla

        [[alternative HTML version deleted]]

By using gstat package, I can do 5-fold cross validation. How can
I write the code/create the loop for "Repeated 5-fold cross validation"
for 10 repeat. Code for 5-fold cross validation is given below. I knew
about 'repeated k-fold cross validation' from here
<http://stats.stackexchange.com/questions/103459/how-do-i-know-which-method-of-cross-validation-is-best>.


library(sp)
data(meuse)  
coordinates(meuse) <- ~x+y
m <- vgm(.59, "Sph", 874, .04)


# five-fold cross validation:
x <- krige.cv(log(zinc)~1, meuse, m, nmax = 40, nfold=5)
str(x)
(R <-cor(x$observed, x$var1.pred))
(RMSE<- sqrt(mean((x$var1.pred-x$observed)^2)))


Orpheus

--------- ?? ?? ---------

    *????* : <uzzal at gist.ac.kr>
    *????* : r-sig-geo <r-sig-geo at r-project.org>
    *????* : 2016? Apr 4?(Mon) 22:02:51
    *??* : [R-sig-Geo] Is there option for 'repeated K-fold cross
    validation' in gstat package?

    I am working with spatial dataset. I have done ordinary kriging on
    this dataset using gstat package in R. I want to do 'repeated
    K-fold cross validation' using krige.cv function of gstat package.
    as far as I know using krige.cv function K-fold/n-fold cross
    validation is possible. Is there any option of doing 'repeated
    K-fold cross validation'  in gstat? or K-fold cross validation is
    enough to check the relation between observed values and kriging
    predicted values?


    I came to know about 'repeated K-fold cross validation'  from here.
    <http://stats.stackexchange.com/questions/103459/how-do-i-know-which-method-of-cross-validation-is-best> Any
    kind help will be appreciable.


    Orpheus

    --------- ?? ?? ---------

        *????* : Tom Philippi <tephilippi at gmail.com>
        *????* : Karla Shikev <karlashikev at gmail.com>
        *??* : r-sig-geo <r-sig-geo at r-project.org>
        *????* : 2016? Apr 4?(Mon) 05:17:16
        *??* : Re: [R-sig-Geo] generating object with multiple polygons

        Karla--
        If you want a SpatialPolygonsDataFrame with both slices of polygons, you
        can use spatial rbind.  The issue that may trip you up is that your slice1
        and slice2 objects might not have unique polygon IDs.  Perhaps the simplest
        solution is to use the spChFIDs in sp, with some prefix distinguishing
        slice1 from slice2.  I assume you're generating some attributes as
        variables in the data frame to distinguish the different polygons; you can
        use those values as the prefix.  You can google this, or start with:
        http://www.inside-r.org/packages/cran/sp/docs/as.data.frame.SpatialPolygonsDataFrame
        http://gis.stackexchange.com/questions/32732/proper-way-to-rbind-spatialpolygonsdataframes-with-identical-polygon-ids

        Tom 2

        On Sun, Apr 3, 2016 at 6:53 AM, Karla Shikev wrote: > Dear all, > > This might be a newbie question, so I'd
        appreciate your patience with this. > > I'm obtaining climatic
        data from worldclim and generating polygons based on > different
        climatic limits: > > library(raster) > xx<-getData('worldclim',
        var='bio', res=10)$bio1 > slice1 <- rasterToPolygons(xx, fun =
        function(x) {x > 200 & x < 260}) > slice2 <-
        rasterToPolygons(xx, fun = function(x) {x > 250 & x < 300}) > >
        Now, I'd like to combine "slice1" and "slice2" into the same >
        "SpatialPolygonsDataFrame" object, but I do not want to merge
        them. > > Any help will be greatly appreciated. > > Karla > >
        [[alternative HTML version deleted]] > >