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  2. Multicollinearity - Wikipedia

    en.wikipedia.org/wiki/Multicollinearity

    High collinearity indicates that it is exceptionally important to include all collinear variables, as excluding any will cause worse coefficient estimates, strong confounding, and downward-biased estimates of standard errors. [2]

  3. Collinearity - Wikipedia

    en.wikipedia.org/wiki/Collinearity

    In geometry, collinearity of a set of points is the property of their lying on a single line. [1] A set of points with this property is said to be collinear (sometimes spelled as colinear [ 2 ] ). In greater generality, the term has been used for aligned objects, that is, things being "in a line" or "in a row".

  4. Variance inflation factor - Wikipedia

    en.wikipedia.org/wiki/Variance_inflation_factor

    The VIF provides an index that measures how much the variance (the square of the estimate's standard deviation) of an estimated regression coefficient is increased because of collinearity. Cuthbert Daniel claims to have invented the concept behind the variance inflation factor, but did not come up with the name. [2]

  5. Synteny - Wikipedia

    en.wikipedia.org/wiki/Synteny

    This is typically done using a version of the MCScan algorithm, which finds syntenic blocks between species by comparing their homologous genes and looking for common patterns of collinearity on a chromosomal or contig scale. Homologies are usually determined on the basis of high bit score BLAST hits that occur

  6. Collinearity equation - Wikipedia

    en.wikipedia.org/wiki/Collinearity_equation

    The collinearity equations are a set of two equations, used in photogrammetry and computer stereo vision, to relate coordinates in a sensor plane (in two dimensions) ...

  7. Condition number - Wikipedia

    en.wikipedia.org/wiki/Condition_number

    A problem with a low condition number is said to be well-conditioned, while a problem with a high condition number is said to be ill-conditioned. In non-mathematical terms, an ill-conditioned problem is one where, for a small change in the inputs (the independent variables) there is a large change in the answer or dependent variable. This means ...

  8. Omnibus test - Wikipedia

    en.wikipedia.org/wiki/Omnibus_test

    To detect multi-collinearity among the predictors, one can conduct a linear regression analysis with the predictors of interest for the sole purpose of examining the tolerance statistic used to assess whether multi-collinearity is unacceptably high. Sparseness in the data refers to having a large proportion of empty cells (cells with zero counts).

  9. Collineation - Wikipedia

    en.wikipedia.org/wiki/Collineation

    In projective geometry, a collineation is a one-to-one and onto map (a bijection) from one projective space to another, or from a projective space to itself, such that the images of collinear points are themselves collinear.