Re: [Gretl-users] Data Import - non-numeric values
Hi there,
thanks very much Allen! I'll take the advice to heart. Fortunately in the case where
these garbage values are "created" a part of the analysis (corresponding to
these values) has not been conducted and that is flagged (in another
"non-garbage" variable), so I can post-process these values. What are the
"maximal" values gretl takes as import? +-1e100 and +-1e-100?
Regards
Frederik
-----Ursprüngliche Nachricht-----
Von: gretl-users-bounces(a)lists.wfu.edu [mailto:gretl-users-bounces@lists.wfu.edu] Im
Auftrag von Allin Cottrell
Gesendet: Sonntag, 27. September 2015 21:02
An: Gretl list
Betreff: Re: [Gretl-users] Data Import - non-numeric values
On Sun, 27 Sep 2015, Allin Cottrell wrote:
Note that whether [uninitialized] values are taken as
"numeric" or not
will in general depend on the C library in use. But either way they're
wrong and have to be changed. _If_ you can get such values into gretl
as numeric, you could fix them via something like:
foo = (abs(foo) > 0 && abs(foo) < 1.0e-100)? NA : foo
where "foo" is the name of the series to be fixed and we're assuming
that non-zero observations with absolute value less than 10^{-100} are
garbage. This is not very reliable, however, as it's _possible_ that
some uninitialized doubles happen to fall in the "normal" range and so
escape correction.
After a little testing, let me rephrase that: it's more than "possible",
it's highly probable.
I wrote a little test C program which created an array of 2048 "doubles",
uninitialized. For each such value I printed it into a string variable using sprintf()
with the "%g" conversion then tried reading it back into a double using
strtod(). I counted the cases where strtod() raised the ERANGE error: 271 out of 2048. So
in this case, at least, the great majority of garbage values appeared to be
"fine": properly numeric and not subnormal.
So here's a big WARNING: on no account should one let uninitialized values get printed
into a file for use in econometric analysis.
There's no half-way reliable method for clearing them out.
[Just as a footnote: a "subnormal" number (also known as
"denormalized") is one that's too close to zero to be represented as a C
"double" to anything like the usual precision. And there's absolutely no
guarantee that the random bits in an uninitialized double will correspond to a subnormal
number.]
Allin Cottrell
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