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  2. Taylor expansions for the moments of functions of random ...

    en.wikipedia.org/wiki/Taylor_expansions_for_the...

    In probability theory, it is possible to approximate the moments of a function f of a random variable X using Taylor expansions, provided that f is sufficiently differentiable and that the moments of X are finite. A simulation-based alternative to this approximation is the application of Monte Carlo simulations.

  3. First-order second-moment method - Wikipedia

    en.wikipedia.org/wiki/First-order_second-moment...

    In probability theory, the first-order second-moment (FOSM) method, also referenced as mean value first-order second-moment (MVFOSM) method, is a probabilistic method to determine the stochastic moments of a function with random input variables.

  4. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    The Taylor expansion would be: + where / denotes the partial derivative of f k with respect to the i-th variable, evaluated at the mean value of all components of vector x. Or in matrix notation , f ≈ f 0 + J x {\displaystyle \mathrm {f} \approx \mathrm {f} ^{0}+\mathrm {J} \mathrm {x} \,} where J is the Jacobian matrix .

  5. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    That is, the Taylor series diverges at x if the distance between x and b is larger than the radius of convergence. The Taylor series can be used to calculate the value of an entire function at every point, if the value of the function, and of all of its derivatives, are known at a single point. Uses of the Taylor series for analytic functions ...

  6. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

    Probability, thermodynamics, digital communications: ... An expansion, [6] which converges more rapidly for all real values of x than a Taylor expansion, ...

  7. Algebra of random variables - Wikipedia

    en.wikipedia.org/wiki/Algebra_of_random_variables

    List of convolutions of probability distributions – the probability measure of the sum of independent random variables is the convolution of their probability measures. Law of total expectation; Law of total variance; Law of total covariance; Law of total cumulance; Taylor expansions for the moments of functions of random variables; Delta method

  8. Projected College Football Playoff rankings: Predictions for ...

    www.aol.com/projected-college-football-playoff...

    The expansion to 12 teams is set in place for the 2024 and 2025 college football seasons. Leaders within the sport have not agreed to the framework of the playoff beyond that at this point.

  9. Delta method - Wikipedia

    en.wikipedia.org/wiki/Delta_method

    Demonstration of this result is fairly straightforward under the assumption that () is differentiable near the neighborhood of and ′ is continuous at with ′ ().To begin, we use the mean value theorem (i.e.: the first order approximation of a Taylor series using Taylor's theorem):