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Thus, the mean time between peaks, including the residence time or mean time before the very first peak, is the inverse of the frequency of exceedance N −1 (y max). If the number of peaks exceeding y max grows as a Poisson process, then the probability that at time t there has not yet been any peak exceeding y max is e −N(y max)t. [6] Its ...
For example, a 10-year flood has a 1/10 = 0.1 or 10% chance of being exceeded in any one year and a 50-year flood has a 0.02 or 2% chance of being exceeded in any one year. This does not mean that a 100-year flood will happen regularly every 100 years, or only once in 100 years. Despite the connotations of the name "return period".
The probability of failure was obtained through the multiplication of each of the failure probabilities along the path under consideration. HRA event tree for aligning and starting emergency purge ventilation equipment on in-tank precipitation tanks 48 or 49 after a seismic event.
For a Type I error, it is shown as α (alpha) and is known as the size of the test and is 1 minus the specificity of the test. This quantity is sometimes referred to as the confidence of the test, or the level of significance (LOS) of the test. For a Type II error, it is shown as β (beta) and is 1 minus the power or 1 minus the sensitivity of ...
The principle of maximum caliber (MaxCal) or maximum path entropy principle, suggested by E. T. Jaynes, [1] can be considered as a generalization of the principle of maximum entropy. It postulates that the most unbiased probability distribution of paths is the one that maximizes their Shannon entropy. This entropy of paths is sometimes called ...
The probability P A (i + 1|i) follows from the ratio of the number of paths that reach interface i + 1 to the total number of paths in the ensemble. Theoretical considerations show that TIS computations are at least twice as fast as TPS, and computer experiments have shown that the TIS rate constant can converge up to 10 times faster.
Maximal entropy random walk (MERW) is a popular type of biased random walk on a graph, in which transition probabilities are chosen accordingly to the principle of maximum entropy, which says that the probability distribution which best represents the current state of knowledge is the one with largest entropy.
We must use an ellipsis for the word "radius" as there is no "R" in the acronym but the value is a radius, and we must use another ellipsis for the reference probability, 1/2. Thus we naturally reconstruct the original term by adding "radius" and the probability p {\displaystyle p} somewhere.