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  2. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    A trend line could simply be drawn by eye through a set of data points, but more properly their position and slope is calculated using statistical techniques like linear regression. Trend lines typically are straight lines, although some variations use higher degree polynomials depending on the degree of curvature desired in the line.

  3. 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 ...

  4. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    Deming regression (total least squares) also finds a line that fits a set of two-dimensional sample points, but (unlike ordinary least squares, least absolute deviations, and median slope regression) it is not really an instance of simple linear regression, because it does not separate the coordinates into one dependent and one independent ...

  5. Ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Ordinary_least_squares

    In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with fixed level-one [clarification needed] effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values ...

  6. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems involved in linear regression, including variants for ordinary (unweighted), weighted, and generalized (correlated) residuals.

  7. The Complete Guide to Trend-Following Indicators

    www.aol.com/news/complete-guide-trend-following...

    Linear Regression R2 – analyses the reliability of price vs regression prediction. Linear Regression Slope – determines the average rate of change when using regression analysis and compares ...

  8. 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.

  9. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).