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Type 'q()' to quit R. > options(error = recover) > library(intamap) Loading required package: sp > > data(meuse) > coordinates(meuse) = ~x+y > data(meuse.grid) > coordinates(meuse.grid) = ~x+y > > meuse$zinc = log(meuse$zinc) > > set.seed(112233) > krigingObject = createIntamapObject( + observations = meuse, + predictionLocations = spsample(meuse.grid,5,"regular"), + # targetCRS = "+init=epsg:3035", + # boundCRS = "+proj=laea +lat_0=48 +lon_0=9 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m", + # boundCRS = boundCRS, + # boundaries = boundaries, + formulaString = as.formula("zinc~1"), + params = list(debug.level = 1), + outputWhat = list(mean = TRUE, variance = TRUE, MOK=7,IWQSEL = 7,excprob = 7.0) + ) > class(krigingObject) = c("automap") > > checkSetup(krigingObject) Checking object ... OK > krigingObject = preProcess(krigingObject) > krigingObject = estimateParameters(krigingObject) > krigingObject = spatialPredict(krigingObject) [using ordinary kriging] drawing 100 GLS realisations of beta... [using conditional Gaussian simulation] [1] "Finished simulations" > krigingObject = postProcess(krigingObject) > summary(krigingObject$outputTable) x y mean variance Min. :180026 Min. :330484 Min. :5.991 Min. :0.1473 1st Qu.:180026 1st Qu.:331281 1st Qu.:6.111 1st Qu.:0.1994 Median :180026 Median :332078 Median :6.230 Median :0.2515 Mean :180026 Mean :332078 Mean :6.217 Mean :0.3950 3rd Qu.:180026 3rd Qu.:332874 3rd Qu.:6.330 3rd Qu.:0.5189 Max. :180026 Max. :333671 Max. :6.430 Max. :0.7863 MOK7 IWQSEL7 excprob7 Min. :6.605 Min. :6.432 Min. :0.004292 1st Qu.:6.724 1st Qu.:6.576 1st Qu.:0.033385 Median :6.844 Median :6.720 Median :0.062477 Mean :6.831 Mean :6.743 Mean :0.109041 3rd Qu.:6.944 3rd Qu.:6.899 3rd Qu.:0.161415 Max. :7.044 Max. :7.078 Max. :0.260354 > > > class(krigingObject) = c("yamamoto") > > checkSetup(krigingObject) Checking object ... OK > krigingObject = preProcess(krigingObject) > krigingObject = estimateParameters(krigingObject) > krigingObject = spatialPredict(krigingObject) Conditional simulation 1 Conditional simulation 2 Conditional simulation 3 Conditional simulation 4 Conditional simulation 5 Conditional simulation 6 Conditional simulation 7 Conditional simulation 8 Conditional simulation 9 Conditional simulation 10 Conditional simulation 11 Conditional simulation 12 Conditional simulation 13 Conditional simulation 14 Conditional simulation 15 Conditional simulation 16 Conditional simulation 17 Conditional simulation 18 Conditional simulation 19 Conditional simulation 20 Conditional simulation 21 Conditional simulation 22 Conditional simulation 23 Conditional simulation 24 Conditional simulation 25 Conditional simulation 26 Conditional simulation 27 Conditional simulation 28 Conditional simulation 29 Conditional simulation 30 Conditional simulation 31 Conditional simulation 32 Conditional simulation 33 Conditional simulation 34 Conditional simulation 35 Conditional simulation 36 Conditional simulation 37 Conditional simulation 38 Conditional simulation 39 Conditional simulation 40 Conditional simulation 41 Conditional simulation 42 Conditional simulation 43 Conditional simulation 44 Conditional simulation 45 Conditional simulation 46 Conditional simulation 47 Conditional simulation 48 Conditional simulation 49 Conditional simulation 50 Conditional simulation 51 Conditional simulation 52 Conditional simulation 53 Conditional simulation 54 Conditional simulation 55 Conditional simulation 56 Conditional simulation 57 Conditional simulation 58 Conditional simulation 59 Conditional simulation 60 Conditional simulation 61 Conditional simulation 62 Conditional simulation 63 Conditional simulation 64 Conditional simulation 65 Conditional simulation 66 Conditional simulation 67 Conditional simulation 68 Conditional simulation 69 Conditional simulation 70 Conditional simulation 71 Conditional simulation 72 Conditional simulation 73 Conditional simulation 74 Conditional simulation 75 Conditional simulation 76 Conditional simulation 77 Conditional simulation 78 Conditional simulation 79 Conditional simulation 80 Conditional simulation 81 Conditional simulation 82 Conditional simulation 83 Conditional simulation 84 Conditional simulation 85 Conditional simulation 86 Conditional simulation 87 Conditional simulation 88 Conditional simulation 89 Conditional simulation 90 Conditional simulation 91 Conditional simulation 92 Conditional simulation 93 Conditional simulation 94 Conditional simulation 95 Conditional simulation 96 Conditional simulation 97 Conditional simulation 98 Conditional simulation 99 Conditional simulation 100 > krigingObject = postProcess(krigingObject) > summary(krigingObject$outputTable) x y mean variance Min. :180026 Min. :330484 Min. :5.842 Min. :0.5709 1st Qu.:180026 1st Qu.:331281 1st Qu.:5.902 1st Qu.:0.5751 Median :180026 Median :332078 Median :5.963 Median :0.5793 Mean :180026 Mean :332078 Mean :6.024 Mean :0.6420 3rd Qu.:180026 3rd Qu.:332874 3rd Qu.:6.115 3rd Qu.:0.6775 Max. :180026 Max. :333671 Max. :6.268 Max. :0.7757 MOK7 IWQSEL7 excprob7 Min. :6.645 Min. :6.806 Min. :0.08489 1st Qu.:6.705 1st Qu.:6.831 1st Qu.:0.08962 Median :6.766 Median :6.857 Median :0.09436 Mean :6.827 Mean :6.902 Mean :0.11574 3rd Qu.:6.918 3rd Qu.:6.950 3rd Qu.:0.13117 Max. :7.071 Max. :7.043 Max. :0.16799 > > proc.time() user system elapsed 3.68 0.57 4.25