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  2. Semi-log plot - Wikipedia

    en.wikipedia.org/wiki/Semi-log_plot

    The linear–log type of a semi-log graph, defined by a logarithmic scale on the x axis, and a linear scale on the y axis. Plotted lines are: y = 10 x (red), y = x (green), y = log(x) (blue). In science and engineering, a semi-log plot/graph or semi-logarithmic plot/graph has one axis on a logarithmic scale, the other on a linear scale.

  3. Deming regression - Wikipedia

    en.wikipedia.org/wiki/Deming_regression

    The quantification of a biological cell's intrinsic cellular noise can be quantified upon applying Deming regression to the observed behavior of a two reporter synthetic biological circuit. [ 8 ] When humans are asked to draw a linear regression on a scatterplot by guessing, their answers are closer to orthogonal regression than to ordinary ...

  4. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    In science and engineering, a log–log graph or log–log plot is a two-dimensional graph of numerical data that uses logarithmic scales on both the horizontal and vertical axes. Power functions – relationships of the form y = a x k {\displaystyle y=ax^{k}} – appear as straight lines in a log–log graph, with the exponent corresponding to ...

  5. Theil–Sen estimator - Wikipedia

    en.wikipedia.org/wiki/Theil–Sen_estimator

    An estimator for the slope with approximately median rank, having the same breakdown point as the Theil–Sen estimator, may be maintained in the data stream model (in which the sample points are processed one by one by an algorithm that does not have enough persistent storage to represent the entire data set) using an algorithm based on ε-nets.

  6. Regression dilution - Wikipedia

    en.wikipedia.org/wiki/Regression_dilution

    Frost and Thompson (2000) review several methods for estimating this ratio and hence correcting the estimated slope. [4] The term regression dilution ratio , although not defined in quite the same way by all authors, is used for this general approach, in which the usual linear regression is fitted, and then a correction applied.

  7. Experimental uncertainty analysis - Wikipedia

    en.wikipedia.org/wiki/Experimental_uncertainty...

    that is, find (z − E[z] ) and do the necessary algebra to collect terms and simplify. 7. For most purposes, it is sufficient to keep only the first-order terms; square that quantity. 8. Find the expected value of that result. This will be the approximation for the variance of z.

  8. Segmented regression - Wikipedia

    en.wikipedia.org/wiki/Segmented_regression

    For the "no effect" analysis, application of the least squares method for the segmented regression analysis [6] may not be the most appropriate technique because the aim is rather to find the longest stretch over which the Y-X relation can be considered to possess zero slope while beyond the reach the slope is significantly different from zero ...

  9. Sensitivity analysis - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_analysis

    Taking into account uncertainty arising from different sources, whether in the context of uncertainty analysis or sensitivity analysis (for calculating sensitivity indices), requires multiple samples of the uncertain parameters and, consequently, running the model (evaluating the -function) multiple times. Depending on the complexity of the ...