Rare Event Simulation for T-cell Activation

Rare event simulation for T-cell activation

The problem of \emph{statistical recognition} is considered, as it arises in immunobiology, namely, the discrimination of foreign antigens against a background of the body's own molecules. The precise mechanism of this foreign-self-distinction, though one of the major tasks of the immune system, continues to be a fundamental puzzle. Recent progress has been made by van den Berg, Rand, and Burro...

Rare event simulation for probabilistic models of T-cell activation

Rare-Event Simulation

Rare events are events that are expected to occur infrequently or, more technically, those that have low probabilities (say, order of 10 3 or less) of occurring according to a probability model. In the context of uncertainty quantification, the rare events often correspond to failure of systems designed for high reliability, meaning that the system performance fails to meet some design or opera...

Rare-Event Simulation

for n large. The approximation (1.1) asserts that the “easy problem instances” arise when α is either close to 0 or 1, and that the “hardest problem instances” arise when α ≈ 1/2. This (perhaps surprising) conclusion arises because (1.1) is describing the absolute error associated with the computation. But in rare-event simulation, we are concerned with relative error, not absolute error (i.e. ...

Rare event simulation

Discrete event simulation as a method for performance evaluation has become an indispensable tool in many fields, e.g., teletraffic engineering. New communication networks and services pose extreme requirements regarding the quality of service, e.g., cell loss probabilities in ATM1 networks in the order of 10 . Straightforward simulation for this type of rare event leads to simulation run times...