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Monte Carlo sampling
Design and analysis of large-scale
- A First Course in Monte Carlo, Thomson Brooks/Cole, 2005. For errata, see fcmc_errata.pdf.
Simulation: Modeling, Programming, and Analysis, New
York, Springer-Verlag, 2001. For errata,
Algorithms, and Applications, New
York, Springer-Verlag, 1996.
- An analysis of Swendsen-Wang
and related sampling
methods, J. Roy. Statist. Soc., B,
Part 3, (1999) 623-641.
- Best- and worst-case variances when
bounds are available
for the distribution function, Computational
Analysis, 29, (1998), 35-53.
| Simulation Output
is a collection of programs for statistically analyzing sample path
on a strictly stationary stochastic process. For each sample path in
input, it computes a sample mean and an asymptotically valid confidence
interval for the population mean. It also displays a sequence of
of the asymptotic variance of the sample mean that allows an assessment
of the quality of the final estimate of this quantity and,
an assessment of the validity of the confidence interval.
of programs that can facilitate Mont Carlo sampling. In
for the pseudorandom number generator
known as the Mersenne twister, MT19937, a
program, rng_afm.c, provides a means for
seeds at the beginning of a run
and saving the final numbers in the
at the end of the run.
This allows for non-overlapping
on successive runs.
contains seeds to initialize rng_afm.c.
ct.hm.c estimates the number of two-way
contingency tables with given row sums and column sums.
ct.chisq.c estimates the number of contingency
tables with chi-squared statistics no larger than a given value.
the Frontiers of Simulation: A Festschrift in Honor of George Samuel
Fishman, C. Alexopoulos, D. Goldsman, J. R. Wilson, eds,
Lanchester Prize (INFORMS)
for the 1996 outstanding publication in
Research and Management Sciences in English.
INFORMS College on Simulation Award
for the 1997
outstanding publication in simulation.
Distinguished Service Award (1990)
INFORMS College on Simulation
The RAND Corporation
Administrative Sciences Department Yale
Operations Research Department University
Chapel Hill, NC