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  2. Tanner graph - Wikipedia

    en.wikipedia.org/wiki/Tanner_graph

    Tanner proved the following bounds Let be the rate of the resulting linear code, let the degree of the digit nodes be and the degree of the subcode nodes be .If each subcode node is associated with a linear code (n,k) with rate r = k/n, then the rate of the code is bounded by

  3. 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.

  4. 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.

  5. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...

  6. 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.

  7. Segmented regression - Wikipedia

    en.wikipedia.org/wiki/Segmented_regression

    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). The data may show many types or trends, [2] see the figures.

  8. Anscombe's quartet - Wikipedia

    en.wikipedia.org/wiki/Anscombe's_quartet

    The four datasets composing Anscombe's quartet. All four sets have identical statistical parameters, but the graphs show them to be considerably different. Anscombe's quartet comprises four datasets that have nearly identical simple descriptive statistics, yet have very different distributions and appear very different when graphed.

  9. Polynomial regression - Wikipedia

    en.wikipedia.org/wiki/Polynomial_regression

    In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial in x.