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  2. PDF-XChange Viewer - Wikipedia

    en.wikipedia.org/wiki/PDF-XChange_Viewer

    PDF-XChange Viewer (now superseded by the PDF-XChange Editor) is a freemium PDF reader for Microsoft Windows. It supports saving PDF forms and importing or exporting form data in FDF/XFDF format. Since version 2.5, there has been partial support for XFA, and exporting form data in XML Data Package (XDP) or XML format.

  3. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    When "E" is used to denote "expected value", authors use a variety of stylizations: the expectation operator can be stylized as E (upright), E (italic), or (in blackboard bold), while a variety of bracket notations (such as E(X), E[X], and EX) are all used. Another popular notation is μ X.

  4. 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.

  5. PDF - Wikipedia

    en.wikipedia.org/wiki/PDF

    A PDF page description can use a matrix to scale, rotate, or skew graphical elements. A key concept in PDF is that of the graphics state, which is a collection of graphical parameters that may be changed, saved, and restored by a page description. PDF has (as of version 2.0) 25 graphics state properties, of which some of the most important are:

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    The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web.

  7. Law of total covariance - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_covariance

    Note: The conditional expected values E( X | Z) and E( Y | Z) are random variables whose values depend on the value of Z. Note that the conditional expected value of X given the event Z = z is a function of z. If we write E( X | Z = z) = g(z) then the random variable E( X | Z) is g(Z). Similar comments apply to the conditional covariance.

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  9. e (mathematical constant) - Wikipedia

    en.wikipedia.org/wiki/E_(mathematical_constant)

    The global maximum of xx occurs at x = e. Steiner's problem asks to find the global maximum for the function =. This maximum occurs precisely at x = e. (One can check that the derivative of ln f(x) is zero only for this value of x.) Similarly, x = 1/e is where the global minimum occurs for the function