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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. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    All have the same trend, but more filtering leads to higher r 2 of fitted trend line. The least-squares fitting process produces a value, r-squared (r 2), which is 1 minus the ratio of the variance of the residuals to the variance of the dependent variable. It says what fraction of the variance of the data is explained by the fitted trend line.

  4. Linear interpolation - Wikipedia

    en.wikipedia.org/wiki/Linear_interpolation

    A description of linear interpolation can be found in the ancient Chinese mathematical text called The Nine Chapters on the Mathematical Art (九章算術), [1] dated from 200 BC to AD 100 and the Almagest (2nd century AD) by Ptolemy. The basic operation of linear interpolation between two values is commonly used in computer graphics.

  5. Theil–Sen estimator - Wikipedia

    en.wikipedia.org/wiki/Theil–Sen_estimator

    A variation of the Theil–Sen estimator, the repeated median regression of Siegel (1982), determines for each sample point (x i, y i), the median m i of the slopes (y j − y i)/(x j − x i) of lines through that point, and then determines the overall estimator as the median of these medians.

  6. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    The above equations are efficient to use if the mean of the x and y variables (¯ ¯) are known.If the means are not known at the time of calculation, it may be more efficient to use the expanded version of the ^ ^ equations.

  7. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, R, JavaScript, Fortran, and C#. It has no external dependencies. A convenient thin wrapper to Python is available via the highspy PyPI package. Although generally single-threaded, some solver components can utilize multi-core ...

  8. Numerical methods for linear least squares - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    The numerical methods for linear least squares are important because linear regression models are among the most important types of model, both as formal statistical models and for exploration of data-sets. The majority of statistical computer packages contain

  9. Trend line (technical analysis) - Wikipedia

    en.wikipedia.org/wiki/Trend_line_(technical...

    In finance, a trend line is a bounding line for the price movement of a security. It is formed when a diagonal line can be drawn between a minimum of three or more price pivot points. It is formed when a diagonal line can be drawn between a minimum of three or more price pivot points.

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