paremu | R Documentation |
This function estimates the parameters (\eta
and \alpha
) of the Eta-Mu (\eta:\mu
) distribution given the L-moments of the data in an L-moment object such as that returned by lmoms
. The relations between distribution parameters and L-moments are seen under lmomemu
.
The basic approach for parameter optimization is to extract initial guesses for the parameters from the table EMU_lmompara_byeta
in the .lmomcohash
environment. The parameters having a minimum Euclidean error as controlled by three arguments are used for initial guesses in a Nelder-Mead simplex multidimensional optimization using the R function optim
and default arguments.
Limited testing indicates that of the “error term controlling options” that the default values as shown in the Usage section seem to provide superior performance in terms of recovering the a priori known parameters in experiments. It seems that only Euclidean optimization using L-skew and L-kurtosis is preferable, but experiments show the general algorithm to be slow.
paremu(lmom, checklmom=TRUE, checkbounds=TRUE,
alsofitT3=FALSE, alsofitT3T4=FALSE, alsofitT3T4T5=FALSE,
justfitT3T4=TRUE, boundary.tolerance=0.001,
verbose=FALSE, trackoptim=TRUE, ...)
lmom |
An L-moment object created by |
checklmom |
Should the |
checkbounds |
Should the L-skew and L-kurtosis boundaries of the distribution be checked. |
alsofitT3 |
Logical when true will add the error term |
alsofitT3T4 |
Logical when true will add the error term |
alsofitT3T4T5 |
Logical when true will add the error term |
justfitT3T4 |
Logical when true will only consider the sum of squares errors for L-skew and L-kurtosis as mathematically shown for |
boundary.tolerance |
A fudge number to help guide how close to the boundaries an arbitrary list of |
verbose |
A logical to control a level of diagnostic output. |
trackoptim |
A logical to control specific messaging through each iteration of the objective function. |
... |
Other arguments to pass. |
An R list
is returned.
type |
The type of distribution: |
para |
The parameters of the distribution. |
source |
The source of the parameters: “paremu”. |
W.H. Asquith
Yacoub, M.D., 2007, The kappa-mu distribution and the eta-mu distribution: IEEE Antennas and Propagation Magazine, v. 49, no. 1, pp. 68–81
lmomemu
, cdfemu
, pdfemu
, quaemu
## Not run:
par1 <- vec2par(c(.3, 2.15), type="emu")
lmr1 <- lmomemu(par1, nmom=4)
par2.1 <- paremu(lmr1, alsofitT3=FALSE, verbose=TRUE, trackoptim=TRUE)
par2.1$para # correct parameters not found: eta=0.889 mu=3.54
par2.2 <- paremu(lmr1, alsofitT3=TRUE, verbose=TRUE, trackoptim=TRUE)
par2.2$para # correct parameters not found: eta=0.9063 mu=3.607
par2.3 <- paremu(lmr1, alsofitT3T4=TRUE, verbose=TRUE, trackoptim=TRUE)
par2.3$para # correct parameters not found: eta=0.910 mu=3.62
par2.4 <- paremu(lmr1, justfitT3T4=TRUE, verbose=TRUE, trackoptim=TRUE)
par2.4$para # correct parameters not found: eta=0.559 mu=3.69
x <- seq(0,3,by=.01)
plot(x, pdfemu(x, par1), type="l", lwd=6, col=8, ylim=c(0,2))
lines(x, pdfemu(x, par2.1), col=2, lwd=2, lty=2)
lines(x, pdfemu(x, par2.2), col=4)
lines(x, pdfemu(x, par2.3), col=3, lty=3, lwd=2)
lines(x, pdfemu(x, par2.4), col=5, lty=2, lwd=2)
## End(Not run)
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