1

I started to read about Kriging and the implementation into R. In all the tutorials I found, a (regular) grid is used to do ordinary or universal kriging. My situation is as follows, I try to interpolate house prices, which of course do not lie on a regular grid. For all houses I have a set of covariates including features such as number of rooms and space. For a subset (approx. 20%), I have the corresponding house price. When doing Regression-kriging in estimating price ~ rooms + space, I cannot provide the data for the regular grid points.

Is there a way of using unevenly spaced prediction points or how is this best tackled?

Improve this question

1 Answer 1

Reset to default
3

Have you read the help for gstat::krige:

newdata: data frame or Spatial object with prediction/simulation locations; should contain attribute columns with the independent variables (if present) and (if locations is a formula) the coordinates with names as defined in ‘locations’

You create a newdata data frame with the locations and attributes of your prediction locations and you get back predictions at those locations.

Improve this answer

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.