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  2. Double mass analysis - Wikipedia

    en.wikipedia.org/wiki/Double_mass_analysis

    Double mass analysis is a simple graphical method to evaluate the consistency of hydrological data. The DM approach plots the cumulative data of one variable against the cumulative data of a second variable. A break in the slope of a linear function fit to the data is thought to represent a change in the relation between the variables.

  3. Bresenham's line algorithm - Wikipedia

    en.wikipedia.org/wiki/Bresenham's_line_algorithm

    Plotting the line from (0,1) to (6,4) showing a plot of grid lines and pixels. All of the derivation for the algorithm is done. One performance issue is the 1/2 factor in the initial value of D. Since all of this is about the sign of the accumulated difference, then everything can be multiplied by 2 with no consequence.

  4. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    The left plot, titled 'Concave Line with Log-Normal Noise', displays a scatter plot of the observed data (y) against the independent variable (x). The red line represents the 'Median line', while the blue line is the 'Mean line'. This plot illustrates a dataset with a power-law relationship between the variables, represented by a concave line.

  5. Lineweaver–Burk plot - Wikipedia

    en.wikipedia.org/wiki/Lineweaver–Burk_plot

    An example of a Lineweaver–Burk plot of 1/v against 1/a. In biochemistry, the Lineweaver–Burk plot (or double reciprocal plot) is a graphical representation of the Michaelis–Menten equation of enzyme kinetics, described by Hans Lineweaver and Dean Burk in 1934. [1]

  6. Plot (graphics) - Wikipedia

    en.wikipedia.org/wiki/Plot_(graphics)

    Ridgeline plot: Several line plots, vertically stacked and slightly overlapping. Q–Q plot : In statistics, a Q–Q plot (Q stands for quantile) is a graphical method for diagnosing differences between the probability distribution of a statistical population from which a random sample has been taken and a

  7. Semi-log plot - Wikipedia

    en.wikipedia.org/wiki/Semi-log_plot

    On a semi-log plot the spacing of the scale on the y-axis (or x-axis) is proportional to the logarithm of the number, not the number itself. It is equivalent to converting the y values (or x values) to their log, and plotting the data on linear scales. A log–log plot uses the logarithmic scale for both axes, and hence is not a semi-log plot.

  8. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    For example, for Newton's method as applied to a function f to oscillate between 0 and 1, it is only necessary that the tangent line to f at 0 intersects the x-axis at 1 and that the tangent line to f at 1 intersects the x-axis at 0. [19] This is the case, for example, if f(x) = x 3 − 2x + 2.

  9. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    For example, if we already know the values of F 41 and F 40, we can directly calculate the value of F 42. Some programming languages can automatically memoize the result of a function call with a particular set of arguments, in order to speed up call-by-name evaluation (this mechanism is referred to as call-by-need ).