Stochastic-process rare event sampling (SPRES) is a rare-event sampling method in computer simulation, designed specifically for non-equilibrium calculations...

flux sampling (FFS), generalized splitting, adaptive multilevel splitting (AMS), stochastic-process rare-event sampling (SPRES), line sampling, subset...

sampling is also related to umbrella sampling in computational physics. Depending on the application, the term may refer to the process of sampling from...

Transition path sampling (TPS) is a rare-event sampling method used in computer simulations of rare events: physical or chemical transitions of a system...

distribution) to approximate events, which are considered rare or unlikely, of some stochastic process. In some cases these rare events are close to being independent...

use adaptive routines such as stratified sampling, recursive stratified sampling, adaptive umbrella sampling or the VEGAS algorithm. A similar approach...

application in signal and image processing, Bayesian inference, machine learning, risk analysis and rare event sampling, engineering and robotics, artificial...

Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability of each event depends only on the...

Tilting is used in Monte Carlo Estimation for rare-event simulation, and rejection and importance sampling in particular. In mathematical finance Exponential...

observation of a rare event does not contradict that the event is in fact rare. It is the observation of a plurality of purportedly rare events that increasingly...

role of rare events in historical affairs. In his 2010 book, Taleb defines the term as an event with two characteristics: first, it is so rare and outside...

for large values of λ include rejection sampling and using Gaussian approximation. Inverse transform sampling is simple and efficient for small values...

buses. The resolution of the paradox is that our sampled distribution at time t is size-biased (see sampling bias), in that the likelihood an interval is...

Zarahn, E. Stochastic Designs in Event-Related fMRI. (1999). NeuroImage. 10. 607-6-19. D'Esposito, M., Zarahn, E., & Aguirre, G. K. (1999). Event-related...

model the number of successes in a sample of size n drawn with replacement from a population of size N. If the sampling is carried out without replacement...

Bernhard; Maass, Wolfgang (3 November 2011). "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons". PLOS...

invariance and insensitivity to the type of sampling. The odds ratio is the ratio of the odds of an event occurring in one group to the odds of it occurring...

2013 a technique called stochastic pooling, the conventional deterministic pooling operations were replaced with a stochastic procedure, where the activation...

business and medical research, sampling is widely used for gathering information about a population. Acceptance sampling is used to determine if a production...

Branching and interacting particle interpretation of rare event probabilities (PDF) (stochastic Hybrid Systems: Theory and Safety Critical Applications...

having this rare disease due to high false positive rates. In this case, the probability of the event B (having dengue) given that the event A (testing...

selection) or "random drift" (e.g., sampling error). "Drift" came to be adopted as a technical term in the stochastic sense exclusively. Today it is usually...

agent in the experimental hypothesis. Random sampling is a related, but distinct, process. Random sampling is recruiting participants in a way that they...

intrinsic variability of the system (aleatory), such as the occurrence of stochastic events. In models involving many input variables, sensitivity analysis is...

such rare events. This is because, for a given variance, the Laplace distribution, which the Moving Median assumes, places higher probability on rare events...

to problems in economics, usually those including uncertainty or stochastic processes and nonlinear dynamics. Some of its application to the study of financial...

to mediocrity) is the phenomenon where if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer...

Will". In probability theory, a stochastic process, or sometimes random process, is the counterpart to a deterministic process (or deterministic system). Instead...

when there is less than 0.1 ng() of DNA in a sample. This can lead to more stochastic effects (random events) such as allelic dropout or allelic drop-in...

maintaining high accuracy. Scaled-sigma sampling (SSS) accelerates rare-event analysis by amplifying process variations to increase failure rates during...