SH.diss: Sircombe and Hazelton distance
In provenance: Statistical Toolbox for Sedimentary Provenance Analysis
SH.diss R Documentation
Sircombe and Hazelton distance
Description
Calculates Sircombe and Hazelton's L2 distance between the Kernel
Functional Estimates (KFEs, not to be confused with Kernel Density
Estimates!) of two samples with specified analytical uncertainties
Usage
SH.diss(x, i, j, c.con = 0)
Arguments
x
an object of class distributional
i
index of the first sample
j
index of the second sample
c.con
smoothing bandwidth of the kernel functional estimate
Value
a scalar value expressing the L2 distance between the KFEs
of samples i and j
Author(s)
Keith Sircombe and Martin Hazelton
References
Sircombe, K. N., and M. L. Hazelton. "Comparison of
detrital zircon age distributions by kernel functional estimation."
Sedimentary Geology 171.1 (2004): 91-111.
See Also
KS.diss
Examples
datfile <- system.file("Namib/DZ.csv",package="provenance")
errfile <- system.file("Namib/DZerr.csv",package="provenance")
DZ <- read.distributional(datfile,errfile)
d <- SH.diss(DZ,1,2)
print(d)
provenance documentation built on May 29, 2024, 4:23 a.m.
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| SH.diss | R Documentation |
Sircombe and Hazelton distance
Description
Calculates Sircombe and Hazelton's L2 distance between the Kernel Functional Estimates (KFEs, not to be confused with Kernel Density Estimates!) of two samples with specified analytical uncertainties
Usage
SH.diss(x, i, j, c.con = 0)
Arguments
x |
an object of class |
i |
index of the first sample |
j |
index of the second sample |
c.con |
smoothing bandwidth of the kernel functional estimate |
Value
a scalar value expressing the L2 distance between the KFEs of samples i and j
Author(s)
Keith Sircombe and Martin Hazelton
References
Sircombe, K. N., and M. L. Hazelton. "Comparison of detrital zircon age distributions by kernel functional estimation." Sedimentary Geology 171.1 (2004): 91-111.
See Also
KS.diss
Examples
datfile <- system.file("Namib/DZ.csv",package="provenance")
errfile <- system.file("Namib/DZerr.csv",package="provenance")
DZ <- read.distributional(datfile,errfile)
d <- SH.diss(DZ,1,2)
print(d)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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