I have a data frame with daily observations, which I would like to interpolate. I use automap to build a variogram for every days and then apply on new data. I try to run a loop and put the results in a new dataframe. Unfortunately, the data frame with the results only contains the last predicted day.
coordinates(mydata) <- ~lat+long
coordinates(new_data) <- ~lat+long
df <- data.frame(matrix(nrow=50,ncol=10)) #new data frame for predicted valeus
for(i in 1:ncol(mydata))
kriging_new <- autoKrige(mydata[,i],mydata,newdata)
pred <- kriging_new$krige_output$var1.pred
df[,i] <- data.frame(pred)
The result looks like this, all the columns should be filled with values, not just the last one:
X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
1 NA NA NA NA NA NA NA NA NA 12.008726
2 NA NA NA NA NA NA NA NA NA 6.960499
3 NA NA NA NA NA NA NA NA NA 10.894787
4 NA NA NA NA NA NA NA NA NA 14.378945
5 NA NA NA NA NA NA NA NA NA 17.719522
I also get a warning, saying:
Warning message:
In autofitVariogram(formula, data_variogram, model = model, kappa = kappa, :
Some models where removed for being either NULL or having a negative sill/range/nugget,
set verbose == TRUE for more information
If I do autoKrige manually for each row, everything works fine. It seems the loop is not working as it usually does. Is this some problem in the automap package?
Thanks a lot!
I think you just forgot to enclose the code in your for
loop in curly brackets. As a result you execute the loop 10 times, overwriting kriging_new
with itself every time:
for(i in 1:ncol(mydata))
kriging_new <- autoKrige(mydata[,i],mydata,newdata)
Only then do you assign the result from your last iteration:
pred <- kriging_new$krige_output$var1.pred
and finally assign those to the last column of your data frame holding your predictions (the loop counter i
is still set to 10 at this point):
df[, i] <- data.frame(pred)
Always write loops with multiple lines of statements like this:
for (condition) {
statement1
statement2
...
}