Probabilistic analysis of algorithms

In analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem. It starts from an assumption about a probabilistic distribution of the set of all possible inputs. This assumption is then used to design an efficient algorithm or to derive the complexity of a known algorithm.This approach is not the same as that of probabilistic algorithms, but the two may be combined.

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enIn analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem. It starts from an assumption about a probabilistic distribution of the set of all possible inputs. This assumption is then used to design an efficient algorithm or to derive the complexity of a known algorithm.This approach is not the same as that of probabilistic algorithms, but the two may be combined.
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enIn analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem. It starts from an assumption about a probabilistic distribution of the set of all possible inputs. This assumption is then used to design an efficient algorithm or to derive the complexity of a known algorithm.This approach is not the same as that of probabilistic algorithms, but the two may be combined. For non-probabilistic, more specifically deterministic, algorithms, the most common types of complexity estimates are the average-case complexity and the almost-always complexity. To obtain the average-case complexity, given an input distribution, the expected time of an algorithm is evaluated, whereas for the almost-always complexity estimate, it is evaluated that the algorithm admits a given complexity estimate that almost surely holds. In probabilistic analysis of probabilistic (randomized) algorithms, the distributions or average of all possible choices in randomized steps is also taken into account, in addition to the input distributions.
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Probabilistic analysis of algorithms
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enProbabilistic analysis of algorithms
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Algorithm
Almost surely
Amortized analysis
Analysis of algorithms
Average-case complexity
Best, worst and average case
Category:Analysis of algorithms
Category:Randomized algorithms
Deterministic algorithm
Principle of deferred decision
Probabilistic algorithm
Random self-reducibility
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Probabilistic analysis of algorithms
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Category:Analysis of algorithms
Category:Randomized algorithms
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