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  2. Power transform - Wikipedia

    en.wikipedia.org/wiki/Power_transform

    In statistics, a power transform is a family of functions applied to create a monotonic transformation of data using power functions.It is a data transformation technique used to stabilize variance, make the data more normal distribution-like, improve the validity of measures of association (such as the Pearson correlation between variables), and for other data stabilization procedures.

  3. Box–Cox distribution - Wikipedia

    en.wikipedia.org/wiki/BoxCox_distribution

    In statistics, the BoxCox distribution (also known as the power-normal distribution) is the distribution of a random variable X for which the BoxCox transformation on X follows a truncated normal distribution. It is a continuous probability distribution having probability density function (pdf) given by

  4. Data transformation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    The reciprocal transformation, some power transformations such as the Yeo–Johnson transformation, and certain other transformations such as applying the inverse hyperbolic sine, can be meaningfully applied to data that include both positive and negative values [10] (the power transformation is invertible over all real numbers if λ is an odd ...

  5. All models are wrong - Wikipedia

    en.wikipedia.org/wiki/All_models_are_wrong

    Box used the aphorism again in 1979, where he expanded on the idea by discussing how models serve as useful approximations, despite failing to perfectly describe empirical phenomena. [7] He reiterated this sentiment in his later works , where he discussed how models should be judged based on their utility rather than their absolute correctness.

  6. Box–Cox transformation - Wikipedia

    en.wikipedia.org/?title=BoxCox_transformation...

    Retrieved from "https://en.wikipedia.org/w/index.php?title=BoxCox_transformation&oldid=721269118"

  7. Non-linear least squares - Wikipedia

    en.wikipedia.org/wiki/Non-linear_least_squares

    Consider a set of data points, (,), (,), …, (,), and a curve (model function) ^ = (,), that in addition to the variable also depends on parameters, = (,, …,), with . It is desired to find the vector of parameters such that the curve fits best the given data in the least squares sense, that is, the sum of squares = = is minimized, where the residuals (in-sample prediction errors) r i are ...

  8. Linking number - Wikipedia

    en.wikipedia.org/wiki/Linking_number

    In Euclidean space, the linking number is always an integer, but may be positive or negative depending on the orientation of the two curves (this is not true for curves in most 3-manifolds, where linking numbers can also be fractions or just not exist at all). The linking number was introduced by Gauss in the form of the linking integral.

  9. Parameter space - Wikipedia

    en.wikipedia.org/wiki/Parameter_space

    In complex dynamics, the parameter space is the complex plane C = { z = x + y i : x, y ∈ R}, where i 2 = −1. The famous Mandelbrot set is a subset of this parameter space, consisting of the points in the complex plane which give a bounded set of numbers when a particular iterated function is repeatedly applied from that starting point. The ...