# collinear

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## col·lin·e·ar

(kə-lĭn′ē-ər, kŏ-)
1. Passing through or lying on the same straight line.
2. Containing a common line; coaxial.

col·lin′e·ar′i·ty (-ăr′ĭ-tē) n.

## collinear

(kɒˈlɪnɪə)
1. (Mathematics) lying on the same straight line
2. (Mathematics) having a common line
collinearity n

## col•lin•e•ar

(kəˈlɪn i ər, koʊ-)

lying in the same straight line.
[1720–30]
col•lin`e•ar′i•ty, n.

## col·lin·e·ar

(kə-lĭn′ē-ər)
Mathematics
1. Sharing a common line, such as two intersecting planes.
2. Lying on the same line, such as a set of points.
ThesaurusAntonymsRelated WordsSynonymsLegend:
 Adj. 1 collinear - lying on the same linelinear, one-dimensional - of or in or along or relating to a line; involving a single dimension; "a linear measurement"
Translations

## collinear

[kɒˈlɪnɪəʳ] adj (Math) (points) → collineare
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References in periodicals archive ?
HILBERT can reduce the collinearity without significantly increasing the path length compared with SCAN and DOUBLE-SCAN.
The presence of collinearity does not reduce the predictive power of the model as a whole, but the individual coefficients estimated for each collinear variable could be unstable when new variables or observations are introduced to the model, especially for VIF values [greater than or equal to] 10 (26).
Moreover, we assessed collinearity to ensure there was no redundant information that would cause unstable regression coefficients.
Collinearity statistics Tolerance VIF Aesthetic 8.925 0.000 preferences 9.489 0.000 0.690 1.450 (adjusted -6.845 0.000 0.935 1.069 [R.sup.2] = -5.258 0.001 0.781 1.280 0.968) (urban rivers) 2.762 0.025 0.726 1.377 Aesthetic -2.451 0.050 preferences 6.958 0.000 0.952 1.050 (adjusted [R.sup.2] = 5.453 0.002 0.886 1.128 0.938) (rural rivers) 4.287 0.005 0.848 1.179
Visual inspection of a scatterplot matrix suggested potential collinearity between species and ftld, species and ftld*comp, and ftld and ftld*comp.
William James once said: "We must be careful not to confuse data with the abstractions we use to analyze them." Collinearity is a problem that occurs during the creation of regression models.
The collinearity of these regions was compared to the orthologous regions in the rice and sorghum genomes (Figure 1).
 to estimate the object-space collinearity error with a different objective function.
Thus, the results may be distorted (e.g., probable overadjustment, potential collinearity).
For each of the six regression analyses using the SPSS Complex Samples Module, regression assumptions were first examined using a regular multiple regression analysis, which included testing independent errors using Durbin-Watson statistics, testing collinearity using tolerance values, and checking linearity and homoscedasticity using P-P plots.
In IBM's SPSS 19.0, Collinearity Diagnostic tests of the data revealed no independent variable with a condition index above 4.0; in addition, no two variables shared variance proportions above .50.
Further the collinearity diagnostics confirm that there are no serious problems with multicolinearity.

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