2,931 research outputs found
An "All Possible Steps" Approach to the Accelerated Use of Gillespie's Algorithm
Many physical and biological processes are stochastic in nature.
Computational models and simulations of such processes are a mathematical and
computational challenge. The basic stochastic simulation algorithm was
published by D. Gillespie about three decades ago [D.T. Gillespie, J. Phys.
Chem. {\bf 81}, 2340, (1977)]. Since then, intensive work has been done to make
the algorithm more efficient in terms of running time. All accelerated versions
of the algorithm are aimed at minimizing the running time required to produce a
stochastic trajectory in state space. In these simulations, a necessary
condition for reliable statistics is averaging over a large number of
simulations. In this study I present a new accelerating approach which does not
alter the stochastic algorithm, but reduces the number of required runs. By
analysis of collected data I demonstrate high precision levels with fewer
simulations. Moreover, the suggested approach provides a good estimation of
statistical error, which may serve as a tool for determining the number of
required runs.Comment: Accepted for publication at the Journal of Chemical Physics. 19
pages, including 2 Tables and 4 Figure
A note on the invariant distribution of a quasi-birth-and-death process
The aim of this paper is to give an explicit formula of the invariant
distribution of a quasi-birth-and-death process in terms of the block entries
of the transition probability matrix using a matrix-valued orthogonal
polynomials approach. We will show that the invariant distribution can be
computed using the squared norms of the corresponding matrix-valued orthogonal
polynomials, no matter if they are or not diagonal matrices. We will give an
example where the squared norms are not diagonal matrices, but nevertheless we
can compute its invariant distribution
Early appraisal of the fixation probability in directed networks
In evolutionary dynamics, the probability that a mutation spreads through the
whole population, having arisen in a single individual, is known as the
fixation probability. In general, it is not possible to find the fixation
probability analytically given the mutant's fitness and the topological
constraints that govern the spread of the mutation, so one resorts to
simulations instead. Depending on the topology in use, a great number of
evolutionary steps may be needed in each of the simulation events, particularly
in those that end with the population containing mutants only. We introduce two
techniques to accelerate the determination of the fixation probability. The
first one skips all evolutionary steps in which the number of mutants does not
change and thereby reduces the number of steps per simulation event
considerably. This technique is computationally advantageous for some of the
so-called layered networks. The second technique, which is not restricted to
layered networks, consists of aborting any simulation event in which the number
of mutants has grown beyond a certain threshold value, and counting that event
as having led to a total spread of the mutation. For large populations, and
regardless of the network's topology, we demonstrate, both analytically and by
means of simulations, that using a threshold of about 100 mutants leads to an
estimate of the fixation probability that deviates in no significant way from
that obtained from the full-fledged simulations. We have observed speedups of
two orders of magnitude for layered networks with 10000 nodes
Persepsi Keluarga Terhadap Skizofrenia
Families who have a family member suffering from schizophrenia experience social isolation related stigma. Therefore, people with schizophrenia often hide and isolated in order to be not known by the public, whereas positive perception of the families towards schizophrenia is needed in the treatment of schizophrenia. The purpose of this study was to determine the perception of the families about schizophrenia. This research used descriptive quantitative method. Samples in this study amounted to 80 respondents using consecutive sampling. The data was collected for one week by using the questionnaire. The reliability test results of the questinnaire obtained for 0.70. Analysis of the data used descriptive statistical analysis in the from of a mean. The results showed that most of the respondents have a positive perception of schizophrenia by 50 respondents and the remaining 30 respondents had negative perceptions toward schizophrenia. This shows there is still a negative perception of families towards schizophrenia . One of the ways that can be done to change the familie's perception is by giving health education to the families and psychiatric hospitals need to develop health promotion in the community to creat a positive perception towards schizophrenia
Separable and Low-Rank Continuous Games
In this paper, we study nonzero-sum separable games, which are continuous
games whose payoffs take a sum-of-products form. Included in this subclass are
all finite games and polynomial games. We investigate the structure of
equilibria in separable games. We show that these games admit finitely
supported Nash equilibria. Motivated by the bounds on the supports of mixed
equilibria in two-player finite games in terms of the ranks of the payoff
matrices, we define the notion of the rank of an n-player continuous game and
use this to provide bounds on the cardinality of the support of equilibrium
strategies. We present a general characterization theorem that states that a
continuous game has finite rank if and only if it is separable. Using our rank
results, we present an efficient algorithm for computing approximate equilibria
of two-player separable games with fixed strategy spaces in time polynomial in
the rank of the game
Structure of Extreme Correlated Equilibria: a Zero-Sum Example and its Implications
We exhibit the rich structure of the set of correlated equilibria by
analyzing the simplest of polynomial games: the mixed extension of matching
pennies. We show that while the correlated equilibrium set is convex and
compact, the structure of its extreme points can be quite complicated. In
finite games the ratio of extreme correlated to extreme Nash equilibria can be
greater than exponential in the size of the strategy spaces. In polynomial
games there can exist extreme correlated equilibria which are not finitely
supported; we construct a large family of examples using techniques from
ergodic theory. We show that in general the set of correlated equilibrium
distributions of a polynomial game cannot be described by conditions on
finitely many moments (means, covariances, etc.), in marked contrast to the set
of Nash equilibria which is always expressible in terms of finitely many
moments
Transition probabilities for general birth-death processes with applications in ecology, genetics, and evolution
A birth-death process is a continuous-time Markov chain that counts the
number of particles in a system over time. In the general process with
current particles, a new particle is born with instantaneous rate
and a particle dies with instantaneous rate . Currently no robust and
efficient method exists to evaluate the finite-time transition probabilities in
a general birth-death process with arbitrary birth and death rates. In this
paper, we first revisit the theory of continued fractions to obtain expressions
for the Laplace transforms of these transition probabilities and make explicit
an important derivation connecting transition probabilities and continued
fractions. We then develop an efficient algorithm for computing these
probabilities that analyzes the error associated with approximations in the
method. We demonstrate that this error-controlled method agrees with known
solutions and outperforms previous approaches to computing these probabilities.
Finally, we apply our novel method to several important problems in ecology,
evolution, and genetics
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