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  2. PDF.js - Wikipedia

    en.wikipedia.org/wiki/PDFjs

    According to a benchmark by Mozilla, PDF.js is performant for viewing most common PDF files, while it may have some issues with large or 'graphics-heavy' documents. [ 22 ] PDF.js supports most of the PDF specifications (including form support or XFA [ 23 ] ), but some features have not been implemented yet, which may impact rendering behavior ...

  3. File:Example.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Example.pdf

    Short title: example derived form Ghostscript examples: Image title: derivative of Ghostscript examples "text_graphic_image.pdf", "alphabet.ps" and "waterfal.ps"

  4. Dynamic HTML - Wikipedia

    en.wikipedia.org/wiki/Dynamic_HTML

    Use a form to capture user input, and then process, verify and respond to that data without having to send data back to the server. Include rollover buttons or drop-down menus. A less common use is to create browser-based action games.

  5. File:Pdf-js logo.svg - Wikipedia

    en.wikipedia.org/wiki/File:Pdf-js_logo.svg

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  6. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    One can generate Student A(t | ν) samples by taking the ratio of variables from the normal distribution and the square-root of the χ² distribution. If we use instead of the normal distribution, e.g., the Irwin–Hall distribution, we obtain over-all a symmetric 4 parameter distribution, which includes the normal, the uniform, the triangular ...

  7. Cumulative distribution function - Wikipedia

    en.wikipedia.org/wiki/Cumulative_distribution...

    Cumulative distribution function for the exponential distribution Cumulative distribution function for the normal distribution. In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable, or just distribution function of , evaluated at , is the probability that will take a value less than or equal to .

  8. Geometric distribution - Wikipedia

    en.wikipedia.org/wiki/Geometric_distribution

    The above form of the geometric distribution is used for modeling the number of trials up to and including the first success. By contrast, the following form of the geometric distribution is used for modeling the number of failures until the first success: (=) = (= +) = ()

  9. Hypergeometric distribution - Wikipedia

    en.wikipedia.org/wiki/Hypergeometric_distribution

    In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of successes (random draws for which the object drawn has a specified feature) in draws, without replacement, from a finite population of size that contains exactly objects with that feature, wherein each draw is either a success or a failure.

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