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  2. Covariance and correlation - Wikipedia

    en.wikipedia.org/wiki/Covariance_and_correlation

    where E is the expected value operator. Notably, correlation is dimensionless while covariance is in units obtained by multiplying the units of the two variables. If Y always takes on the same values as X, we have the covariance of a variable with itself (i.e. ), which is called the variance and is more commonly denoted as the square of the ...

  3. Big O in probability notation - Wikipedia

    en.wikipedia.org/wiki/Big_O_in_probability_notation

    The order in probability notation is used in probability theory and statistical theory in direct parallel to the big-O notation that is standard in mathematics.Where the big-O notation deals with the convergence of sequences or sets of ordinary numbers, the order in probability notation deals with convergence of sets of random variables, where convergence is in the sense of convergence in ...

  4. Codomain - Wikipedia

    en.wikipedia.org/wiki/Codomain

    In mathematics, a codomain or set of destination of a function is a set into which all of the output of the function is constrained to fall. It is the set Y in the notation f: X → Y. The term range is sometimes ambiguously used to refer to either the codomain or the image of a function. A codomain is part of a function f if f is defined as a ...

  5. Forcing function (differential equations) - Wikipedia

    en.wikipedia.org/wiki/Forcing_function...

    In a system of differential equations used to describe a time-dependent process, a forcing function is a function that appears in the equations and is only a function of time, and not of any of the other variables. [1][2] In effect, it is a constant for each value of t. In the more general case, any nonhomogeneous source function in any ...

  6. Brownian bridge - Wikipedia

    en.wikipedia.org/wiki/Brownian_bridge

    Brownian motion, pinned at both ends. This represents a Brownian bridge. A Brownian bridge is a continuous-time gaussian process B(t) whose probability distribution is the conditional probability distribution of a standard Wiener process W(t) (a mathematical model of Brownian motion) subject to the condition (when standardized) that W(T) = 0, so that the process is pinned to the same value at ...

  7. Martingale difference sequence - Wikipedia

    en.wikipedia.org/wiki/Martingale_difference_sequence

    In probability theory, a martingale difference sequence (MDS) is related to the concept of the martingale. A stochastic series X is an MDS if its expectation with respect to the past is zero. Formally, consider an adapted sequence on a probability space . is an MDS if it satisfies the following two conditions: E [ X t | F t − 1 ] = 0 , a .

  8. Conjugate element (field theory) - Wikipedia

    en.wikipedia.org/wiki/Conjugate_element_(field...

    In mathematics, in particular field theory, the conjugate elements or algebraic conjugates of an algebraic element α, over a field extension L/K, are the roots of the minimal polynomial pK,α(x) of α over K. Conjugate elements are commonly called conjugates in contexts where this is not ambiguous. Normally α itself is included in the set of ...

  9. Infinite difference method - Wikipedia

    en.wikipedia.org/wiki/Infinite_difference_method

    Infinite difference method. In mathematics, infinite difference methods are numerical methods for solving differential equations by approximating them with difference equations, in which infinite differences approximate the derivatives. In calculus there are two sections, one is differentiation and the other is integration.