fields tests {fields} | R Documentation |
Some of the basic methods in feilds can be tested by directly implementing the linear algebra using matrix expressions. These comparisons are done in the the test files: Krig.se.test.R Krig.se.grid.test.R Krig.test.R. The function test.for.zero is useful for comparing the tests in a meaninful and documented way.
test.for.zero( xtest,xtrue, tol= 1.0e-8, relative=TRUE, tag=NULL)
xtest |
Vector of target values |
xtrue |
Vector of reference values |
tol |
Tolerance to judge whether the test passes. |
relative |
If true a relative error comparison is used. (See details below.) |
tag |
A text string to be printed out with the test results as a reference |
The scripts in the tests subdirectory are
Krig.test.R: Tests basic parts of the Krig and Tps functions including replicated and weighted observations.
Krig.se.test.R: Tests computations of standard errors for the Kriging estimate.
Krig.se.grid.test.R Tests approximate standard errors for the Krig function found by Monte Carlo conditional simulation.
To run the tests just attach the fields library and source the testing file. For the fields package source code these are in a subdirectory "tests".
test.for.zero
is used to print out the result for each individual comparison.
All the tests should pass with text beginning,
"****** passed test at tolerance ..."
Failed tests are potentially very bad ...
The actual test done is the sum of absolute differnces:
test value =
sum( abs(c(xtest) - c( xtrue) ) ) /denom
Where demon
is either mean( abs(c(xtrue)))
for relative error
or 1.0 otherwise.
Note the use of "c" here to stack any structure in xtest and xtrue into a vector.