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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. Scale parameter - Wikipedia

    en.wikipedia.org/wiki/Scale_parameter

    Is location-invariant, Scales linearly with the scale parameter, and; Converges as the sample size grows. Various measures of statistical dispersion satisfy these. In order to make the statistic a consistent estimator for the scale parameter, one must in general multiply the statistic by a constant scale factor. This scale factor is defined as ...

  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. Invariant estimator - Wikipedia

    en.wikipedia.org/wiki/Invariant_estimator

    For example, a requirement of invariance may be incompatible with the requirement that the estimator be mean-unbiased; on the other hand, the criterion of median-unbiasedness is defined in terms of the estimator's sampling distribution and so is invariant under many transformations.

  8. Renormalization group - Wikipedia

    en.wikipedia.org/wiki/Renormalization_group

    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. As the scale varies, it is as if one is decreasing (as RG is a ...

  9. Scale-free network - Wikipedia

    en.wikipedia.org/wiki/Scale-free_network

    However, there's a key difference. In statistical field theory, the term "scale" often pertains to system size. In the realm of networks, "scale" is a measure of connectivity, generally quantified by a node's degree—that is, the number of links attached to it. Networks featuring a higher number of high-degree nodes are deemed to have greater ...