The <code>BD</code> data frame has 89 rows and 5 columns. There are 89 runs with  
four buffer components (KCL, MgCl2, KP04, dnTP) systematically varied in 
a space-filliing design. The response is the DNA amplification rate.

datasets

Fields is for curve, surface and function
 fitting with an emphasis on splines, spatial data and spatial statistics. The
 major methods include cubic, robust, and thin plate splines, 
 multivariate Kriging and Kriging for large data sets. One main feature is any
 covariance function implemented in R can be used for spatial prediction. 
 There are also useful functions for plotting and working with 
 spatial data as images. This package also contains an implementation of a
 sparse matrix  methods for large data sets and currently requires the 
 sparse matrix (spam) package for testing (but not for the standard spatial 
 functions.) Use help(fields) to get started and for an overview. 

Douglas Nychka

fields

Tools for spatial data

BD function

Thanks to Perry Haaland and Michael OConnell.<p></p><p>Becton Dickinson Research Center 
Research Triangle Park, NC</p>

source

Data frame of the effect of buffer compositions on DNA strand displacement 
amplification. A 4-d regression data set with 
with replication. This is a useful test data set for exercising function
fitting methods.

BD: Data frame of the effect of buffer compositions on DNA strand displacement amplification. A 4-d regression data set with with replication. This is a useful test data set for exercising function fitting methods.

Description

Arguments

source

See Also

Examples