Thanks to Kit Baum, new -sliceplot-
and -cquantile- programs are now
downloadable from SSC.
sliceplot: time series or other plot in slices
==============================================
Often a time series plot -- or indeed some other
kinds of plot -- would benefit from a short and
wide scale. In his excellent books on graphics,
Bill Cleveland recommends as an ideal that line
segments should be close to 45 deg. This advice
is also to be found as far back as R.A. Fisher's
"Statistical methods for research workers", and
perhaps earlier.
This rule is difficult to achieve on the kind of
time series that goes up and down like a demented
yo-yo on steroids, unless either you have easy
access to a printer with special paper sizes
or you slice the plot and then recombine in
one image. I can do nothing about your printer
access but I provide in -sliceplot- ways of
cutting up the original data by sections of
the horizontal axis variable (e.g. time)
into component graphs, then putting them together
again by -graph combine-, thus reducing the
nitty-gritty somewhat.
Even if it is not what you want in this
territory, some of the code in -sliceplot-
may be suitable for your own programs.
Stata 8 is required for the ado and
Stata 9 is required for the help file.
Thus Stata 8 users should find this works;
it is just that the on-line help will
show some SMCL directives that Stata 8 doesn't
understand.
cquantile: corresponding quantiles
==================================
As a fan of quantile-quantile plots, I make
much use of Stata's -qqplot-, but aside from the
excellent graphics features of Stata >=8, I note that
it lacks some of the statistical features that might be
desired.
Thus -qqplot- does not directly support
the q-q plotting of two groups of the same variable.
This is soluble by -generate-ing two variables, one
for each group, just before the -qqplot-. [R]
diagnostic plots gives an example. -separate- may
be used more efficiently to the same end.
More importantly, -qqplot- often suggests structure
that one would like to show or examine in other ways.
Thus if one set of quantiles differs from another
mostly by an additive shift -- or possibly by
a multiplicative one -- then such structure can be
examined by looking at the difference between
corresponding quantiles versus their mean, or the
ratio of the corresponding quantiles versus their
geometric mean.
To get such results, there are various strategies
including (a) pestering StataCorp to extend the
command and (b) cloning -qqplot-, getting inside
and adding code. In this case, following the
"less is more" philosophy, I just took the part
of -qqplot- that calculates the quantiles and
added a -generate- option. Then you can plot,
or otherwise manipulate, the quantiles as desired.
Thus -cquantile- generates corresponding quantiles, namely, those
quantiles that would be shown on a quantile-quantile plot.
Given either two numeric variables, or one numeric variable and
one grouping variable defining two groups, two new variables
are generated containing the quantiles.
Stata 9 is required.
Nick
[email protected]
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