Skip to Main Content
Data Analysis and Statistics for Geography, Environmental Science, and Engineering
book

Data Analysis and Statistics for Geography, Environmental Science, and Engineering

by Miguel F. Acevedo
December 2012
Beginner content levelBeginner
557 pages
19h 5m
English
CRC Press
Content preview from Data Analysis and Statistics for Geography, Environmental Science, and Engineering
425Geostatistics
12.6.4 functions
The following function Okriging.R performs ordinary kriging the function is
Okriging <- function (dataset, vario, step, maxdist,border.
sw=F,border.poly="none"){
# dataset: columns 1 and 2 are x,y coordinates, 3 is variable
# vario is variogram model, step is interval for the prediction grid
# maxdist is max distance for prediction
# extract names of coord and variable
x <- names(dataset)[1]
y <- names(dataset)[2]
v <- names(dataset)[3]
# First, select a grid for the prediction.
# Use min and max of the original dataset and a distance step
grid <- list(x=seq(min(dataset[,1]),max(dataset[,1]),by=step),
y=seq(min(dataset[,2]),max(dataset[,2]),by=step)) ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Applied Modeling Techniques and Data Analysis 1

Applied Modeling Techniques and Data Analysis 1

Yannis Dimotikalis, Alex Karagrigoriou, Christina Parpoula, Christos H. Skiadas
Geospatial Data and Analysis

Geospatial Data and Analysis

Aurelia Moser, Jon Bruner, Bill Day

Publisher Resources

ISBN: 9781439885017