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  2. Continuous uniform distribution - Wikipedia

    en.wikipedia.org/wiki/Continuous_uniform...

    Any probability density function integrates to , so the probability density function of the continuous uniform distribution is graphically portrayed as a rectangle where ⁠ ⁠ is the base length and ⁠ ⁠ is the height. As the base length increases, the height (the density at any particular value within the distribution boundaries) decreases.

  3. Ratio of uniforms - Wikipedia

    en.wikipedia.org/wiki/Ratio_of_uniforms

    Rejection sampling of a bounded statistical distribution with finite support. A convenient technique to sample a statistical distribution is rejection sampling.When the probability density function of the distribution is bounded and has finite support, one can define a bounding box around it (a uniform proposal distribution), draw uniform samples in the box and return only the x coordinates of ...

  4. Ratio distribution - Wikipedia

    en.wikipedia.org/wiki/Ratio_distribution

    The ratio is one type of algebra for random variables: Related to the ratio distribution are the product distribution, sum distribution and difference distribution.More generally, one may talk of combinations of sums, differences, products and ratios.

  5. Inverse transform sampling - Wikipedia

    en.wikipedia.org/wiki/Inverse_transform_sampling

    Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, or the Smirnov transform) is a basic method for pseudo-random number sampling, i.e., for generating sample numbers at random from any probability distribution given its cumulative distribution function.

  6. Probability integral transform - Wikipedia

    en.wikipedia.org/wiki/Probability_integral_transform

    In probability theory, the probability integral transform (also known as universality of the uniform) relates to the result that data values that are modeled as being random variables from any given continuous distribution can be converted to random variables having a standard uniform distribution. [1]

  7. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    As the number of discrete events increases, the function begins to resemble a normal distribution. Comparison of probability density functions, () for the sum of ⁠ ⁠ fair 6-sided dice to show their convergence to a normal distribution with increasing , in accordance to the central limit theorem. In the bottom-right graph, smoothed profiles ...

  8. Maximum spacing estimation - Wikipedia

    en.wikipedia.org/wiki/Maximum_spacing_estimation

    The maximum spacing method tries to find a distribution function such that the spacings, D (i), are all approximately of the same length. This is done by maximizing their geometric mean . In statistics , maximum spacing estimation ( MSE or MSP ), or maximum product of spacing estimation (MPS) , is a method for estimating the parameters of a ...

  9. Univariate distribution - Wikipedia

    en.wikipedia.org/wiki/Univariate_distribution

    Continuous uniform distribution. One of the simplest examples of a discrete univariate distribution is the discrete uniform distribution, where all elements of a finite set are equally likely. It is the probability model for the outcomes of tossing a fair coin, rolling a fair die, etc.