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  2. Reflection principle (Wiener process) - Wikipedia

    en.wikipedia.org/wiki/Reflection_principle...

    In the theory of probability for stochastic processes, the reflection principle for a Wiener process states that if the path of a Wiener process f(t) reaches a value f(s) = a at time t = s, then the subsequent path after time s has the same distribution as the reflection of the subsequent path about the value a. [1]

  3. Seidel's algorithm - Wikipedia

    en.wikipedia.org/wiki/Seidel's_algorithm

    Seidel's algorithm is an algorithm designed by Raimund Seidel in 1992 for the all-pairs-shortest-path problem for undirected, unweighted, connected graphs. [1] It solves the problem in (⁡) expected time for a graph with vertices, where < is the exponent in the complexity () of matrix multiplication.

  4. Orders of magnitude (probability) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude...

    1.6×101: Gaussian distribution: probability of a value being more than 1 standard deviation from the mean on a specific side [20] 1.7×101: Chance of rolling a '6' on a six-sided die: 4.2×101: Probability of being dealt only one pair in poker 5.0×101: Chance of getting a 'head' in a coin toss.

  5. Rule of succession - Wikipedia

    en.wikipedia.org/wiki/Rule_of_succession

    In probability theory, the rule of succession is a formula introduced in the 18th century by Pierre-Simon Laplace in the course of treating the sunrise problem. [1] The formula is still used, particularly to estimate underlying probabilities when there are few observations or events that have not been observed to occur at all in (finite) sample data.

  6. Viterbi algorithm - Wikipedia

    en.wikipedia.org/wiki/Viterbi_algorithm

    The Viterbi algorithm is named after Andrew Viterbi, who proposed it in 1967 as a decoding algorithm for convolutional codes over noisy digital communication links. [2] It has, however, a history of multiple invention, with at least seven independent discoveries, including those by Viterbi, Needleman and Wunsch, and Wagner and Fischer. [3]

  7. First-hitting-time model - Wikipedia

    en.wikipedia.org/wiki/First-hitting-time_model

    This probability density is calculable from the Survival probability (a more common probability measure in statistics). Consider the absorbing boundary condition p ( x c , t ) = 0 {\displaystyle p(x_{c},t)=0} (The subscript c for the absorption point x c {\displaystyle x_{c}} is an abbreviation for cliff used in many texts as an analogy to an ...

  8. Trump’s historic comeback leads to staggering 1,514% ... - AOL

    www.aol.com/trump-historic-comeback-leads...

    Since the president-elect’s comeback victory became official on Wednesday, the number of related Google searches jumped 1,514% percent, according to VisaGuide.World. Donald Trump won the ...

  9. Cumulative frequency analysis - Wikipedia

    en.wikipedia.org/wiki/Cumulative_frequency_analysis

    When the observed data of X are arranged in ascending order (X 1 ≤ X 2 ≤ X 3 ≤ ⋯ ≤ X N, the minimum first and the maximum last), and Ri is the rank number of the observation Xi, where the adfix i indicates the serial number in the range of ascending data, then the cumulative probability may be estimated by: