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  2. Scale invariance - Wikipedia

    en.wikipedia.org/wiki/Scale_invariance

    Another example of a scale-invariant classical field theory is the massless scalar field (note that the name scalar is unrelated to scale invariance). The scalar field, φ ( x , t ) is a function of a set of spatial variables, x , and a time variable, t .

  3. Power law - Wikipedia

    en.wikipedia.org/wiki/Power_law

    This property of () follows directly from the requirement that () be asymptotically scale invariant; thus, the form of () only controls the shape and finite extent of the lower tail. For instance, if L ( x ) {\displaystyle L(x)} is the constant function, then we have a power law that holds for all values of x {\displaystyle x} .

  4. Self-similarity - Wikipedia

    en.wikipedia.org/wiki/Self-similarity

    Scale invariance is an exact form of self-similarity where at any magnification there is a smaller piece of the object that is similar to the whole. For instance, a side of the Koch snowflake is both symmetrical and scale-invariant; it can be continually magnified 3x without changing shape. The non-trivial similarity evident in fractals is ...

  5. Benford's law - Wikipedia

    en.wikipedia.org/wiki/Benford's_law

    The points show the exact formula, P(n) = log 10 (1 + 1/n). The graph tends towards the dashed asymptote passing through (1, log 10 e) with slope −1 in log–log scale. The example in yellow shows that the probability of a number starts with 314 is around 0.00138. The dotted lines show the probabilities for a uniform distribution for comparison.

  6. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

    Asymptotic normality of the MASE: The Diebold-Mariano test for one-step forecasts is used to test the statistical significance of the difference between two sets of forecasts. [ 5 ] [ 6 ] [ 7 ] To perform hypothesis testing with the Diebold-Mariano test statistic, it is desirable for D M ∼ N ( 0 , 1 ) {\displaystyle DM\sim N(0,1)} , where D M ...

  7. Normalization (statistics) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(statistics)

    In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these normalized values allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series. Some ...

  8. Renormalization group - Wikipedia

    en.wikipedia.org/wiki/Renormalization_group

    A change in scale is called a scale transformation. The renormalization group is intimately related to scale invariance and conformal invariance, symmetries in which a system appears the same at all scales (self-similarity), [a] where under the fixed point of the renormalization group flow the field theory is conformally invariant.

  9. Wiener process - Wikipedia

    en.wikipedia.org/wiki/Wiener_process

    A single realization of a one-dimensional Wiener process A single realization of a three-dimensional Wiener process. In mathematics, the Wiener process (or Brownian motion, due to its historical connection with the physical process of the same name) is a real-valued continuous-time stochastic process discovered by Norbert Wiener.