hyperbFit function

Fit the Hyperbolic Distribution to Data

Fit the Hyperbolic Distribution to Data

Fits a hyperbolic 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.

hyperbFit(x, freq = NULL, breaks = NULL, ThetaStart = NULL, startMethod = "Nelder-Mead", startValues = "BN", method = "Nelder-Mead", hessian = FALSE, plots = FALSE, printOut = FALSE, controlBFGS = list(maxit=200), controlNM = list(maxit=1000), maxitNLM = 1500, ...) ## S3 method for class 'hyperbFit' print(x, digits = max(3, getOption("digits") - 3), ...) ## S3 method for class 'hyperbFit' 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(), ...)

Arguments

  • x: Data vector for hyperbFit. Object of class "hyperbFit" for print.hyperbFit and plot.hyperbFit.

  • freq: A vector of weights with length equal to length(x).

  • breaks: Breaks for histogram, defaults to those generated by hist(x, right = FALSE, plot = FALSE).

  • ThetaStart: A user specified starting parameter vector Theta taking the form c(pi,zeta,delta,mu).

  • startMethod: Method used by hyperbFitStart in calls to optim.

  • startValues: Code giving the method of determining starting values for finding the maximum likelihood estimate of Theta.

  • method: Different optimisation methods to consider. See Details .

  • hessian: Logical. If TRUE the value of the hessian is returned.

  • plots: Logical. If FALSE suppresses printing of the histogram, log-histogram, Q-Q plot and P-P plot.

  • printOut: Logical. If FALSE suppresses printing of results of fitting.

  • controlBFGS: A list of control parameters for optim when using the "BFGS" optimisation.

  • controlNM: A list of control parameters for optim

    when using the "Nelder-Mead" optimisation.

  • maxitNLM: A positive integer specifying the maximum number of iterations when using the "nlm" optimisation.

  • 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 1:4.

  • plotTitles: Titles to appear above the plots.

  • ask: Logical. If TRUE, the user is asked before each plot, see par(ask = .).

  • ...: Passes arguments to par, hist, logHist, qqhyperb and pphyperb.

Details

startMethod can be either "BFGS" or "Nelder-Mead".

startValues can be one of the following:

  • "US": User-supplied.
  • "BN": Based on Barndorff-Nielsen (1977).
  • "FN": A fitted normal distribution.
  • "SL": Based on a fitted skew-Laplace distribution.
  • "MoM": Method of moments.

For the details concerning the use of ThetaStart, startMethod, and startValues, see hyperbFitStart.

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 = "nlm"is used, warnings may be produced. These do not appear to be a problem.

Returns

A list with components: - Theta: A vector giving the maximum likelihood estimate of Theta, as (pi,zeta,delta,mu).

  • maxLik: The value of the maximised log-likelihood.

  • hessian: If hessian was set to TRUE, the value of the hessian. Not present otherwise.

  • method: Optimisation method used.

  • conv: Convergence code. See the relevant documentation (either optim or nlm) for details on convergence.

  • iter: Number of iterations of optimisation routine.

  • x: The data used to fit the hyperbolic distribution.

  • xName: A character string with the actual x argument name.

  • ThetaStart: Starting value of Theta returned by call to hyperbFitStart.

  • svName: Descriptive name for the method finding start values.

  • startValues: Acronym for the method of finding start values.

  • KNu: Value of the Bessel function in the fitted density.

  • breaks: The cell boundaries found by a call to hist.

  • midpoints: The cell midpoints found by a call to hist.

  • empDens: The estimated density found by a call to hist.

References

Barndorff-Nielsen, O. (1977) Exponentially decreasing distributions for the logarithm of particle size, Proc. Roy. Soc. Lond., A353 , 401--419.

Fieller, N. J., Flenley, E. C. and Olbricht, W. (1992) Statistics of particle size data. Appl. Statist., 41 , 127--146.

Author(s)

David Scott d.scott@auckland.ac.nz , Ai-Wei Lee, Jennifer Tso, Richard Trendall, Thomas Tran

See Also

optim, nlm, par, hist, logHist, qqhyperb, pphyperb, dskewlap and hyperbFitStart.

Examples

Theta <- c(2,2,2,2) dataVector <- rhyperb(500, Theta) ## See how well hyperbFit works hyperbFit(dataVector) hyperbFit(dataVector, plots = TRUE) fit <- hyperbFit(dataVector) par(mfrow = c(1,2)) plot(fit, which = c(1,3)) ## Use nlm instead of default hyperbFit(dataVector, method = "nlm")