logHist  R Documentation 
Plots a loghistogram, as in for example Feiller, Flenley and Olbricht (1992).
The intended use of the loghistogram is to examine the fit of a particular density to a set of data, as an alternative to a histogram with a density curve. For this reason, only the logdensity histogram is implemented, and it is not possible to obtain a logfrequency histogram.
The loghistogram can be plotted with histogramlike dashed vertical bars, or as points marking the tops of the loghistogram bars, or with both bars and points.
logHist(x, breaks = "Sturges", include.lowest = TRUE, right = TRUE, main = paste("LogHistogram of", xName), xlim = range(breaks), ylim = NULL, xlab = xName, ylab = "Logdensity", nclass = NULL, htype = "b", ...)
x 
A vector of values for which the loghistogram is desired. 
breaks 
One of:
In the last three cases the number is a suggestion only. 
include.lowest 
Logical. If 
right 
Logical. If 
main, xlab, ylab 
These arguments to 
xlim 
Sensible default for the range of x values. 
ylim 
Calculated by 
nclass 
Numeric (integer). For compatibility with 
htype 
Type of histogram. Possible types are:

... 
Further graphical parameters for calls
to 
Uses hist.default
to determine the cells or classes and
calculate counts.
To calculate ylim
the following procedure is used. The upper
end of the range is given by the maximum value of the logdensity,
plus 25% of the absolute value of the maximum. The lower end of the
range is given by the smallest (finite) value of the logdensity, less
25% of the difference between the largest and smallest (finite) values
of the logdensity.
A loghistogram in the form used by Feiller, Flenley and Olbricht (1992) is plotted. See also BarndorffNielsen (1977) for use of loghistograms.
Returns a list with components:
breaks 
The n+1 cell boundaries (= 
counts 
n integers; for each cell, the number of

logDensity 
Log of f^(x[i]), which are estimated density values. If 
mids 
The n cell midpoints. 
xName 
A character string with the actual 
heights 
The location of the tops of the vertical segments used in drawing the loghistogram. 
ylim 
The value of 
David Scott d.scott@auckland.ac.nz, Richard Trendall, Thomas Tran
BarndorffNielsen, O. (1977) Exponentially decreasing distributions for the logarithm of particle size, Proc. Roy. Soc. Lond., A353, 401–419.
BarndorffNielsen, O. and Bl<e6>sild, P (1983). Hyperbolic distributions. In Encyclopedia of Statistical Sciences, eds., Johnson, N. L., Kotz, S. and Read, C. B., Vol. 3, pp. 700–707. New York: Wiley.
Fieller, N. J., Flenley, E. C. and Olbricht, W. (1992) Statistics of particle size data. Appl. Statist., 41, 127–146.
hist
data(SandP500) ### Consider proportional changes in the index change < SandP500[length(SandP500)]/SandP500[1] hist(change) logHist(change) ### Show points only logHist(change, htype = "p", pch = 20, cex = 0.5) ### Fit the hyperbolic distribution to the changes hyperbFit(change)
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