In regression analysis, singularity is the extreme form of multicollinearity – when a perfect linear relationship exists between variables or, in other terms, when the correlation coefficient is equal to 1.0 or -1.0.
Such absolute multicollinearity could arise when independent variable are linearly related in their definition. A simple example: two variables “height in centimeters” and “height in inches” are included in the regression model.