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  2. Theil–Sen estimator - Wikipedia

    en.wikipedia.org/wiki/Theil–Sen_estimator

    It has also been called Sen's slope estimator, [1] [2] slope selection, [3] [4] the single median method, [5] the Kendall robust line-fit method, [6] and the Kendall–Theil robust line. [7] It is named after Henri Theil and Pranab K. Sen , who published papers on this method in 1950 and 1968 respectively, [ 8 ] and after Maurice Kendall ...

  3. Passing–Bablok regression - Wikipedia

    en.wikipedia.org/wiki/Passing–Bablok_regression

    In 1986, Passing and Bablok extended their method introducing an equivariant extension for method transformation which also works when the slope is far from 1. [6] It may be considered a robust version of reduced major axis regression. The slope estimator is the median of the absolute values of all pairwise slopes.

  4. Segmented regression - Wikipedia

    en.wikipedia.org/wiki/Segmented_regression

    Yr = A 1.x + K 1 for x < BP (breakpoint) Yr = A 2.x + K 2 for x > BP (breakpoint) where: Yr is the expected (predicted) value of y for a certain value of x; A 1 and A 2 are regression coefficients (indicating the slope of the line segments); K 1 and K 2 are regression constants (indicating the intercept at the y-axis).

  5. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    A simple two-point estimation is to compute the slope of a nearby secant line through the points (x, f(x)) and (x + h, f(x + h)). [1] Choosing a small number h, h represents a small change in x, and it can be either positive or negative. The slope of this line is (+) ().

  6. Regression dilution - Wikipedia

    en.wikipedia.org/wiki/Regression_dilution

    Illustration of regression dilution (or attenuation bias) by a range of regression estimates in errors-in-variables models. Two regression lines (red) bound the range of linear regression possibilities. The shallow slope is obtained when the independent variable (or predictor) is on the abscissa (x-axis).

  7. Distance from a point to a line - Wikipedia

    en.wikipedia.org/.../Distance_from_a_point_to_a_line

    The line with equation ax + by + c = 0 has slope -a/b, so any line perpendicular to it will have slope b/a (the negative reciprocal). Let (m, n) be the point of intersection of the line ax + by + c = 0 and the line perpendicular to it which passes through the point (x 0, y 0). The line through these two points is perpendicular to the original ...

  8. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    This shows that r xy is the slope of the regression line of the standardized data points (and that this line passes through the origin). Since − 1 ≤ r x y ≤ 1 {\displaystyle -1\leq r_{xy}\leq 1} then we get that if x is some measurement and y is a followup measurement from the same item, then we expect that y (on average) will be closer ...

  9. Slope - Wikipedia

    en.wikipedia.org/wiki/Slope

    Slope illustrated for y = (3/2)x − 1.Click on to enlarge Slope of a line in coordinates system, from f(x) = −12x + 2 to f(x) = 12x + 2. The slope of a line in the plane containing the x and y axes is generally represented by the letter m, [5] and is defined as the change in the y coordinate divided by the corresponding change in the x coordinate, between two distinct points on the line.