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c.t.c. distance. Centre-to-centre distance (c.t.c. distance or ctc distance) is a concept for distances, also called on-center spacing (o.c. spacing or oc spacing), heart distance, and pitch. It is the distance between the centre (the heart) of a column and the centre (the heart) of another column. By expressing a distance in c.t.c., one can ...
In statistics, Cook's distance or Cook's D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis. [1] In a practical ordinary least squares analysis, Cook's distance can be used in several ways: to indicate influential data points that are particularly worth checking for validity; or to indicate regions of the design space where it ...
If the intersection X ∩ Y has a non-empty interior, then there exists a constant r > 0, such that every set X′ whose Hausdorff distance from X is less than r also intersects Y. [5] On the set of all subsets of M, d H yields an extended pseudometric. On the set F(M) of all non-empty compact subsets of M, d H is a metric.
The column space of this matrix is the vector space spanned by the column vectors. In linear algebra, the column space (also called the range or image) of a matrix A is the span (set of all possible linear combinations) of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation.
The Mahalanobis distance is a measure of the distance between a point and a distribution, introduced by P. C. Mahalanobis in 1936. [1] The mathematical details of Mahalanobis distance first appeared in the Journal of The Asiatic Society of Bengal in 1936. [ 2 ]
Make a new node that joins the taxa i and j, and connect the new node to the central node. For example, in part (B) of the figure at right, node u is created to join f and g. Calculate the distance from each of the taxa in the pair to this new node. Calculate the distance from each of the taxa outside of this pair to the new node.
A metric on a set X is a function (called the distance function or simply distance) d : X × X → R + (where R + is the set of non-negative real numbers). For all x, y, z in X, this function is required to satisfy the following conditions: d(x, y) ≥ 0 (non-negativity) d(x, y) = 0 if and only if x = y (identity of indiscernibles.
In general, a distance matrix is a weighted adjacency matrix of some graph. In a network, a directed graph with weights assigned to the arcs, the distance between two nodes of the network can be defined as the minimum of the sums of the weights on the shortest paths joining the two nodes (where the number of steps in the path is bounded). [2]