hi Jordan,
(off-list)
it sounds like your problem is not a good candidate for regression kriging. RK
(or the similar kriging with external drift, KED) require that you have
collocated dependent and independent variables so that you can actually run a
regression.
You could use cokriging, thou
Hi Ashton,
Thanks for taking the time to email me.
I alas don't have the variables for all locations in the "blank" dataset. I
am beginning to wonder if I entirely understand regression kriging (or in
fact if any of my class really understand this).
Having the variables at more locations than th
Hi Jordan,
I always use the 'data' parameter when kriging. Here's how I'd do it:
class(bd) # This should be a SpatialPointsDataFrame
names(bd) # all the variables in the model (Total, m5005CVOL, etc)
class(blank) # This should be a SpatialPointsDataFrame
names(blank) # all the variables in th
Hello, I was wondering if anyone has encountered this issue?
This line works:
TotalKrige <- krige(Total~1, locations=bd,
newdata=blank, model=fit_Total)
This line does not:
TotalRegKrige <-
krige(Total~m5005CVOL+n50010CVOL+n50015CVOL+DTM, locations=bd,
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On 07/19/2013 05:35 PM, Israel Ikoyi wrote:
> Hi, I am trying to do regression kriging with this commands:
> #Regression modeling regSI <- lm(SI~OrgMat+Moisture+pH, data =
> malpie) summary(regSI) # add residual to malpie malpie$resSI <-
> regSI$res
Hi,
I am trying to do regression kriging with this commands:
#Regression modeling
regSI <- lm(SI~OrgMat+Moisture+pH, data = malpie)
summary(regSI)
# add residual to malpie
malpie$resSI <- regSI$residuals
# calculate variogram of residual
gresSI <- gstat(id="resids", formula = resSI~1, data = malpie
