vgFit | R Documentation |
Fits a variance gamma distribution to data. Displays the histogram, log-histogram (both with fitted densities), Q-Q plot and P-P plot for the fit which has the maximum likelihood.
vgFit(x, freq = NULL, breaks = NULL, paramStart = NULL,
startMethod = "Nelder-Mead", startValues = "SL",
method = "Nelder-Mead", hessian = FALSE,
plots = FALSE, printOut = FALSE,
controlBFGS = list(maxit = 200),
controlNM = list(maxit = 1000), maxitNLM = 1500, ...)
## S3 method for class 'vgFit'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'vgFit'
plot(x, which = 1:4,
plotTitles = paste(c("Histogram of ","Log-Histogram of ",
"Q-Q Plot of ","P-P Plot of "), x$obsName,
sep = ""),
ask = prod(par("mfcol")) < length(which) && dev.interactive(),
...)
x |
Data vector for |
freq |
A vector of weights with length equal to |
breaks |
Breaks for histogram, defaults to those generated by
|
paramStart |
A user specified starting parameter vector param taking
the form |
startMethod |
Method used by |
startValues |
Code giving the method of determining starting values for finding the maximum likelihood estimate of param, default method is "SL". See Details. |
method |
Different optimisation methods to consider, default is "Nelder-Mead". See Details. |
hessian |
Logical. If |
plots |
Logical. If |
printOut |
Logical. If |
controlBFGS |
A list of control parameters for |
controlNM |
A list of control parameters for |
maxitNLM |
A positive integer specifying the maximum number of
iterations when using the |
digits |
Desired number of digits when the object is printed. |
which |
If a subset of the plots is required, specify a subset of
the numbers |
plotTitles |
Titles to appear above the plots. |
ask |
Logical. If |
... |
Passes arguments to |
startMethod
can be either "BFGS"
or
"Nelder-Mead"
.
startValues
can be one of the following:
"US"
User-supplied.
"SL"
Based on a fitted skew-Laplace distribution.
"MoM"
Method of moments.
For the details concerning the use of paramStart
,
startMethod
, and startValues
, see
vgFitStart
.
The three optimisation methods currently available are:
"BFGS"
Uses the quasi-Newton method "BFGS"
as
documented in optim
.
"Nelder-Mead"
Uses an implementation of the Nelder and
Mead method as documented in optim
.
"nlm"
Uses the nlm
function in R.
For details of how to pass control information for optimisation using
optim
and nlm
, see optim
and
nlm.
When method = "Nelder-Mead"
is used, very rarely, it would return an
error message of "error in optim(paramStart,...)", use method = "BFGS"
or method = "nlm"
instead in that case.
When method = "nlm"
is used, warnings may be produced. These do
not appear to be a problem.
A list with components:
param |
A vector giving the maximum likelihood estimate of
param, as |
maxLik |
The value of the maximised log-likelihood. |
hessian |
If |
method |
Optimisation method used. |
conv |
Convergence code. See the relevant documentation (either
|
iter |
Number of iterations of optimisation routine. |
obs |
The data used to fit the hyperbolic distribution. |
obsName |
A character string with the actual |
paramStart |
Starting value of param returned by call to
|
svName |
Descriptive name for the method finding start values. |
startValues |
Acronym for the method of finding start values. |
breaks |
The cell boundaries found by a call to
|
midpoints |
The cell midpoints found by a call to
|
empDens |
The estimated density found by a call to
|
David Scott d.scott@auckland.ac.nz, Christine Yang Dong c.dong@auckland.ac.nz
Seneta, E. (2004). Fitting the variance-gamma model to financial data. J. Appl. Prob., 41A:177–187.
optim
, nlm
, par
,
hist
, logHist
,
qqvg
, ppvg
,
dskewlap
and
vgFitStart
.
param <- c(0,0.5,0,0.5)
dataVector <- rvg(500, param = param)
## See how well vgFit works
vgFit(dataVector)
vgFit(dataVector, plots = TRUE)
fit <- vgFit(dataVector)
par(mfrow = c(1,2))
plot(fit, which = c(1,3))
## Use nlm instead of default
param <- c(0,0.5,0,0.5)
dataVector <- rvg(500, param = param)
vgFit(dataVector, method = "nlm", hessian = TRUE)
## Use BFGS instead of deault
param <- c(0,0.5,0,0.5)
dataVector <- rvg(500, param = param)
vgFit(dataVector, method = "BFGS", hessian = TRUE)
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