BiBTeX database and LaTeX macros of Pierre L'Ecuyer
Along the years, with the help of other people,
I have collected a BiBTeX database of references related to my research.
These references are partitioned (sometimes a bit arbitrarily) in the
categories defined below. Some may appear in more than one category.
All the references of any given category are in a single .bib file
to the name of that category.
In each .bib file, the BiBTeX code of all entries start with
a one-letter (sometimes two-letter) prefix for that category,
followed by the first three letters of the name of the first author in uppercase,
followed by the last two digits of the year of publication,
and followed by a lowercase letter (a, b, c, ...).
For example, for the category ``random number generators,''
the file name is ``random.bib'' and the one-letter prefix is ``r.''
In that file, the famous book of Niederreiter (1992) has BiBTeX code ``rNIE92b.''
As another example, the category ``variance reduction techniques'' has
file name ``vrt.bib'' and prefix ``v.''
The prefix is the first letter of the file name, with the following exceptions:
stat.bib has prefix t (because s is already taken by simul) and callc has prefix cc.
These databases are clearly far from being complete, but they may nevertheless
be useful for other people doing research in these areas.
I would be happy to include relevant additional entries that you can provide
me in .bib format, as long as I can keep up with it.
The .bib files are as follows, in the format:
name.bib (prefix) : Category description.
with all the .bib files.
(r) : Everything related to uniform and nonuniform (pseudo)random number generators,
for all kinds of applications, and the construction and study of low-discrepancy
or quasi-Monte Carlo (QMC) point sets and sequences.
Also includes papers useful for the analysis of generators and QMC sets and sequences.
(v) : Variance reduction (or efficiency improvement) methods for simulation and statistics.
It includes randomized quasi-Monte Carlo methods, which can be seen as correlation
induction methods, and techniques for rare-event simulation.
(s) : Topics in (stochastic) simulation, or Monte Carlo methods,
that are not covered by random and vrt.
This includes input modeling, output analysis, and simulation applications, for example.
(p) : Probability. Include Markov chains and other stochastic processes,
and queueing theory.
(t) : Statistics. Includes theory, applied methods, and computational statistics.
(o) : Optimization. Includes optimization methods in deterministic and stochastic
settings (linear and nonlinear programming, dynamic programming,
stochastic programming, control theory, ...).
Also includes derivative and gradient estimation.
(m) : General mathematics. Topics in maths not covered by more specialized categories.
(i) : Computer science and software. Includes software libraries and tools as well.
(f) : Mathematical and computational finance. Includes simulation in finance.
(cc) : Research on modeling, simulation, and optimization of call centers.
with all the files (large and rather messy...).
: A set of predefined ``crayola'' colors.
: My own hacks for doing slides with ppower4.