data = read.csv("data.csv") data$Date = as.Date(data$Date, format = "%d-%m-%Y") class(data$Date) plot(Port1VW ~ Date, data, type = 'l') library(sp) library(spacetime) stidf = STIDF(SpatialPoints(data[c("longitude", "latitude")]), data$Date, data[2:7]) summary(stidf) stsdf= as(stidf, "STSDF") plot(stsdf) plot(stidf) plot(stsdf[,1]) stplot(stsdf, col.regions=bpy.colors()) stplot(as(stsdf, "STFDF"), col.regions=bpy.colors(), mode = "xt") stplot(as(stsdf, "STFDF"), col.regions=bpy.colors(), mode = "ts") stplot(stsdf, col.regions=bpy.colors(), mode = "ts") stplot(as(stsdf, "STFDF"), col.regions=bpy.colors(), mode = "tp") #stplot(as(stsdf, "STFDF")[1:8,], col.regions=bpy.colors(), mode = "tp") validation = read.csv("validation.csv") validation$Date = as.Date(validation$Date, format = "%d-%m-%Y") class(validation$Date) v.stidf = STIDF(SpatialPoints(validation[c("longitude", "latitude")]), validation$Date, validation[,-(1:3)]) v.stsdf = as(v.stidf, "STSDF") over(stsdf@sp, v.stsdf@sp) plot(stsdf) dim(v.stsdf) plot(v.stsdf) plot(v.stsdf, add=TRUE, col = "blue", pch = 3, cex=.5) train = stsdf[,"2013-07"] test = v.stsdf[,"2013-07"] #train = stsdf #test = v.stsdf plot(train) # add points: yy = 1:length(test@sp) xx = index(test@time) time = xx[test@index[,2]] space = yy[test@index[,1]] points(time, space, col = "blue", pch = 3, cex = .5) # temporal aggregation: monthly mean values, omitting NAs ag = aggregate(stsdf, "month", mean, na.rm = TRUE) loc40 = ag@sp coordinates(data) = ~longitude+latitude cls = over(loc40, data)[["TAXSUSDA"]] row.names(ag@sp) = paste(1:40, as.character(cls)) stplot(ag[,,-6], mode = "tp") stplot(ag[1:9,,-6], mode = "tp") library(gstat) variogramST(Port1VW~1, stsdf) plot(v) plot(v, map = FALSE)