Universal kriging with geoR
try dividind the coordinates by 1000 and let me know apparently they are given in UTM, therefore meters, this will change to kilometers If this does not run please send me the data Paulo Justiniano Ribeiro Jr LEG (Laboratorio de Estatistica e Geoinformacao) Universidade Federal do Parana Caixa Postal 19.081 CEP 81.531-990 Curitiba, PR - Brasil Tel: (+55) 41 3361 3573 VOIP: (+55) (41) (3361 3600) 1053 1066 Fax: (+55) 41 3361 3141 e-mail: paulojus AT ufpr br http://www.leg.ufpr.br/~paulojus
On Sat, 3 Oct 2015, GEMA FERNANDEZ-AVILES CALDERON wrote:
Dear list,
I have a computational error and I can not found the solution...
I would like to perform an Universal Kriging with geoR. I have a geodata object: log(price), long, lat and pollution, but 'krige.conv' and 'ksline' functions give me the same error: system is computationally singular.
Any ideas will be appreciated.
Thanks in advance,
Gema
PS: I can send you the data to run the code
############################################################################
# read the data and create a geodata object
attach(Datos)
bordes.munimadrid=read.table("MuniMadrid.txt")
coord=cbind(long,lat)
uk.vivi<-cbind(coord , log(Datos$precio.house.x), Mal_olor )
obj.uk.vivi<-as.geodata(obj=uk.vivi, coords.col = 1:2, data.col = 3,
covar.col = 4 ,covar.names = "Pollution" )
summary(obj.uk.vivi)
#Number of data points: 300
#
#Coordinates summary
# long lat
#min 433426 4466197
#max 451184 4484681
#
#Distance summary
# min max
# 19.18 20836.71
#
#Data summary
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 6.91 7.94 8.19 8.16 8.43 9.28
#
#Covariates summary
# Mal_olor
# Min. :0.080
# 1st Qu.:0.210
# Median :0.260
# Mean :0.281
# 3rd Qu.:0.330
# Max. :0.720
## I woulk like to use this spatial trend but UK doesn't run
sp.tren.rp=trend.spatial("1st", obj.uk.vivi, add=~Mal_olor)
# Universal kriging with geoR() first option
loci <- expand.grid(seq(424854, 456141, l = 101), seq(4462788, 4499622, l = 101))
UK.krig.viviendas <- krige.conv(obj.uk.vivi, loc = loci, borders = bordes.munimadrid,
krige = krige.control(type.krige = "ok", cov.model = "gau",
cov.pars = c(0.06, 3000), nug = 0.05, trend.l = "1st", trend.d ="1st") )
krige.conv: results will be returned only for prediction locations inside the borders
krige.conv: model with mean given by a 1st order polynomial on the coordinates
Error in solve.default(ttivtt, crossprod(ivtt, as.vector(data))) :
sistema es computacionalmente singular: n?mero de condici?n rec?proco = 6.8379e-20
# Universal kriging with geoR() second option
uk.2= ksline(obj.uk.vivi, coords = obj.uk.vivi$coords, data = obj.uk.vivi$data,
loc = loci, borders = bordes.munimadrid,
cov.model = "gau", cov.pars=c(0.06, 3000), nug = 0.05,
lambda = 1, m0 = "kt", nwin = "full",
trend = 1, d = 2 )
ksline: results will be returned only for prediction locations inside the borders
Error in solve.default(crossprod(xmat, iv) %*% xmat) :
sistema es computacionalmente singular: n?mero de condici?n rec?proco = 6.8379e-20
############################################################################
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