Line graph with over 70 lines plotted against time

On Sun, 24 Feb 2019, f-c-b at web.de wrote:

Hello Roger,

thank you for your answer.

I tried:

gwrGp <- gwr(formula=Ziel~ Var1 + Var3 + Var4, data = Daten90,

+ bandwidth = bwG, gweight = gwr.Gauss,hatmatrix = TRUE,
+ fit.points=Daten10, predictions=TRUE, fittedGWRobject=gwrG)

Now the prediction works, but when I give out the result, I get this 
error:

Error in sqrt(x$results$sigma2.b) :
? non-numeric argument to mathematical function
How can I solve this problem?

I am not looking over your shoulder. Always provide the code verbatim, 
if I guess which mess you are in, I may get the wrong mess.

Generally, I advise against GWR in all settings, it should only ever 
be used for exploring data for non-stationarity.

Roger

Thank you,
Christoph

Thank you for your answer.
?I tried to do the transformations before the calculation, but the
Problem is still the same. I think the problem lies in the factor. But
in my model I need the factor, because there is no linear influence of
the year.

Is there any solution for this Problem?
?https://www.dropbox.com/s/fbhwsy3sd333ung/Example.zip?dl=0 The 

zip-file

in the link contains a picture of str(Daten90) and str(Daten10) and 

also

my data and R-skript. Var4 is log(Var2).

I see:

gwrGp <- gwr(formula=Ziel~ Var1 + Var3 + Var4, data = Daten90,

+ bandwidth = bwG, gweight = gwr.Gauss,hatmatrix = TRUE,
+ fit.points=Daten10, predictions=TRUE)
Warning message:
In gwr(formula = Ziel ~ Var1 + Var3 + Var4, data = Daten90, bandwidth =
bwG, :
standard errors set to NA, normalised RSS not available

but using your gwrG object and:

gwrGp <- gwr(formula=Ziel~ Var1 + Var3 + Var4, data = Daten90,

+ bandwidth = bwG, gweight = gwr.Gauss,hatmatrix = TRUE,
+ fit.points=Daten10, predictions=TRUE, fittedGWRobject=gwrG)

I think the model matrix handling of the factor is OK. The problem in 
the
GWmodel::gwr.predict() approach is that the full model matrix 
approach is
used on the formula and data arguments, but not on predictdata, which is
coerced to data frame but never regularised by going through 
model.matrix,
hence the error message:

Browse[2]>
debug: if (any((inde_vars %in% names(predictdata)) == F)) stop("All the
independent variables should be included in the predictdata")
Browse[2]> inde_vars
[1] "Var12006" "Var12007" "Var12008" "Var12009" "Var3" "Var4"
Browse[2]> names(predictdata)
[1] "OBJECTID" "Rechtswert" "Hochwert" "Var1" "Var2"
[6] "Var3" "Ziel" "Var4" "coords.x1" "coords.x2"

Had the proper approach been used, the names would have been the same.

The relevant part of spgwr::gwr() in R/gwr.R is:

if (predictions) {
t1 <- try(slot(fit.points, "data"), silent=TRUE)
if (class(t1) == "try-error")
stop("No data slot in fit.points")
predx <- try(model.matrix(delete.response(mt), fit.points))
if (class(predx) == "try-error")
stop("missing RHS variable in fit.points")
if (ncol(predx) != ncol(x))
stop("new data matrix columns mismatch")
}

(lines 71-80)

which uses model.matrix() and uses try() to catch mis-matches.

Hope this helps,

Roger

Christoph




The first step should be to look at

str(Daten90)
str(Daten10)

and if that doesn't solve the problem, then consider a reproducible
example, or at the very least posting the results of the above to this
list.

Sarah

On Fri, Feb 22, 2019 at 7:38 AM <f-c-b at web.de> wrote:

Dear all,

I am currently working out a geographically weighted regression, in

which

90% of the data set the model should be calculated and for 10% of the

values

to be predicted. For the prediction I use the function gwr.predict 

from
the

package GWModel:

Erg<-gwr.predict(formula=Ziel~ as.factor(Var1) + log(Var2, base =

exp(1))

+ Var3, data = Daten90,predictdata = Daten10,bw = bwG, kernel =
"gaussian",adaptive = FALSE, p = 2, theta = 0, longlat = FALSE)

I always get this error, although Daten10 and Daten90 have the same

structure:

Error in gwr.predict(formula = Ziel~ as.factor(Var1) + log(Var2, 

base =

exp(1)) + Var3, :

All the independent variables should be included in the predictdata.

Can you tell me what the problem with this code is?
Or is there any other way for a GWR and the prediction?

Thank you,
Christoph

--
Sarah Goslee (she/her)
http://www.numberwright.com

-- 
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: Roger.Bivand at nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en