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From |
David Airey <david.airey@vanderbilt.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
re: st: easy histogram |

Date |
Sun, 2 Mar 2003 08:41:47 -0600 |

That's interesting. I've never seen such use. I would think the proper way to deal with this is to log the variable and histogram it, without the xscale(log) option! In that case you get two meaningful axes to inspect. I was thinking that twoway options were being allowed by design too liberally, and should not be, because there is a difference between a plot like a scatter where x and y can be whatever and independent of each other, and plots like histograms, where y is a function of x or calculated from x. Those are not really a plot of two independent variables; in all of those cases, logging the xscale will break the meaning of the graph. I was thinking in those cases, if there are others, the xscale option is no useful. But these thoughts were vague (and somewhat like list) not really that important compared to speeding up graphics and improving estimation methods. Instead I'll look forward to the time when I might need xscale(log) and not have to ask that it be added!

-Dave

> Perhaps not all daughters of the mother twoway should

> inherit certain

> twoway options?

This in turn touches on various tricky design issues, one

being how far statistical software designers (a) should

and (b) can decide ex cathedra which kinds of graph

are inadmissible or inappropriate, especially when what

may seem crazy in one field may turn out to have

a specific rationale in another. Excellence comes

easily to Stata Corp, but omniscience is an asymptotic

property.

I don't know a strong case for binning on the original scale,

yet showing the results with -xscale(log)-. However, blowing

up the left-hand part of the scale like this

might have some private use for examining fine structure.

For example, I have worked with glacier area data which

tend to be very heavily skewed and problematic at the lower end.

Among other issues, it can be difficult to distinguish, especially

without a field visit, between a true glacier and an inert body,

and different scientists compiling area data (usually in some

national agency office) tacitly show different degrees

of scepticism in distinguishing glaciers and non-glaciers.

For such a problem, graphs of the kind discussed might have some

private value, as there is often merit in a scale which uses the

units familiar to researchers. I wouldn't publish such

a histogram myself, but it might be of some use.

More generally, the principle that the area under the histogram

should integrate to 1 -- or to the number of values --

is clearly a good one. However, it is not the only criterion.

Plotting log frequency vs log magnitude is

common in sedimentology. R.A. Bagnold did this

in his classic book on wind-blown sand in 1941

and appropriate hyperbolic distributions have since been

investigated by O. Barndorff-Nielsen and others. Those

ideas appear to be drifting into other areas such as

financial modelling.

Nick

n.j.cox@durham.ac.uk

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