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  2. Ordination (statistics) - Wikipedia

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

    Ordination or gradient analysis, in multivariate analysis, is a method complementary to data clustering, and used mainly in exploratory data analysis (rather than in hypothesis testing). In contrast to cluster analysis, ordination orders quantities in a (usually lower-dimensional) latent space. In the ordination space, quantities that are near ...

  3. Gradsect - Wikipedia

    en.wikipedia.org/wiki/Gradsect

    A gradsect or gradient-directed transect is a low-input, high-return sampling method where the aim is to maximise information about the distribution of biota in any area of study. Most living things are rarely distributed at random , their placement being largely determined by a hierarchy of environmental factors.

  4. Gradient pattern analysis - Wikipedia

    en.wikipedia.org/wiki/Gradient_pattern_analysis

    Gradient pattern analysis (GPA) [1] is a geometric computing method for characterizing geometrical bilateral symmetry breaking of an ensemble of symmetric vectors regularly distributed in a square lattice. Usually, the lattice of vectors represent the first-order gradient of a scalar field, here an M x M square amplitude matrix.

  5. Vector calculus identities - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus_identities

    The curl of the gradient of any continuously twice-differentiable scalar field (i.e., differentiability class) is always the zero vector: =. It can be easily proved by expressing ∇ × ( ∇ φ ) {\displaystyle \nabla \times (\nabla \varphi )} in a Cartesian coordinate system with Schwarz's theorem (also called Clairaut's theorem on equality ...

  6. Gradient method - Wikipedia

    en.wikipedia.org/wiki/Gradient_method

    In optimization, a gradient method is an algorithm to solve problems of the form min x ∈ R n f ( x ) {\displaystyle \min _{x\in \mathbb {R} ^{n}}\;f(x)} with the search directions defined by the gradient of the function at the current point.

  7. Gradient theorem - Wikipedia

    en.wikipedia.org/wiki/Gradient_theorem

    The gradient theorem states that if the vector field F is the gradient of some scalar-valued function (i.e., if F is conservative), then F is a path-independent vector field (i.e., the integral of F over some piecewise-differentiable curve is dependent only on end points). This theorem has a powerful converse:

  8. SUMMARY OF KEY FINDINGS GETTING AHEAD OR LOSING GROUND ...

    images.huffingtonpost.com/2010-03-09-Economic...

    By forging a broad and nonpartisan agreement on the facts, figures and trends related to mobility, the Economic Mobility Project seeks to focus public attention on this critically important issue and generate an active policy debate about how best to ensure that the

  9. Gradient analysis - Wikipedia

    en.wikipedia.org/?title=Gradient_analysis&...

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