libranlip 1.0-4.1 source package in Ubuntu
Changelog
libranlip (1.0-4.1) unstable; urgency=low
* Non-maintainer upload.
* debian/rules:
- Fix bashisms (Closes: #378598).
- Fix debian-rules-ignores-make-clean-error lintian warnings.
* debian/control:
- Use ${binary:Version}, fix substvar-source-version-is-deprecated
lintian warning.
- Move to new Homepage field.
* debian/shlibs:
- Move to libranlip1c2, fix shlibs-declares-dependency-on-other-package
lintian warning.
-- Michele Angrisano <email address hidden> Wed, 23 Jan 2008 17:15:40 +0000
Upload details
- Uploaded by:
- Michele Angrisano
- Uploaded to:
- Hardy
- Original maintainer:
- Juan Esteban Monsalve Tobon
- Architectures:
- any
- Section:
- math
- Urgency:
- Low Urgency
See full publishing history Publishing
| Series | Published | Component | Section | |
|---|---|---|---|---|
| Precise | release | universe | math |
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| libranlip_1.0.orig.tar.gz | 465.9 KiB | 885ad15711a6eddc2af4ded3a7bc4a3ca864e3b4ba2952f3e0c988961a05222a |
| libranlip_1.0-4.1.diff.gz | 3.4 KiB | 40fcff485fa8d1d66c462c09e3daf8005a3fb4c072f99b97ccc9331af4a3a475 |
| libranlip_1.0-4.1.dsc | 614 bytes | b0c59b32fa769651b7130642c03e588f7faeb90878664c42bea1b53f3c522770 |
Binary packages built by this source
- libranlip-dev: No summary available for libranlip-dev in ubuntu maverick.
No description available for libranlip-dev in ubuntu maverick.
- libranlip1c2: generates random variates with multivariate Lipschitz density
RanLip generates random variates with an arbitrary multivariate
Lipschitz density.
.
While generation of random numbers from a variety of distributions is
implemented in many packages (like GSL library
http://www.gnu. org/software/ gsl/ and UNURAN library
http://statistik. wu-wien. ac.at/unuran/), generation of random variate
with an arbitrary distribution, especially in the multivariate case, is
a very challenging task. RanLip is a method of generation of random
variates with arbitrary Lipschitz-continuous densities, which works in
the univariate and multivariate cases, if the dimension is not very
large (say 3-10 variables).
.
Lipschitz condition implies that the rate of change of the function (in
this case, probability density p(x)) is bounded:
.
|p(x)-p(y)|<M| |x-y||.
.
From this condition, we can build an overestimate of the density, so
called hat function h(x)>=p(x), using a number of values of p(x) at some
points. The more values we use, the better is the hat function. The
method of acceptance/rejection then works as follows: generatea random
variate X with density h(x); generate an independent uniform on (0,1)
random number Z; if p(X)<=Z h(X), then return X, otherwise repeat all
the above steps.
.
RanLip constructs a piecewise constant hat function of the required
density p(x) by subdividing the domain of p (an n-dimensional rectangle)
into many smaller rectangles, and computes the upper bound on p(x)
within each of these rectangles, and uses this upper bound as the value
of the hat function.
