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  2. 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.

  3. 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.

  4. Cell cycle analysis - Wikipedia

    en.wikipedia.org/wiki/Cell_cycle_analysis

    Cell cycle analysis by DNA content measurement is a method that most frequently employs flow cytometry to distinguish cells in different phases of the cell cycle.Before analysis, the cells are usually permeabilised and treated with a fluorescent dye that stains DNA quantitatively, such as propidium iodide (PI) or 4,6-diamidino-2-phenylindole (DAPI).

  5. Cancer slope factor - Wikipedia

    en.wikipedia.org/wiki/Cancer_slope_factor

    Cancer slope factors (CSF) are used to estimate the risk of cancer associated with exposure to a carcinogenic or potentially carcinogenic substance. A slope factor is an upper bound, approximating a 95% confidence limit , on the increased cancer risk from a lifetime exposure to an agent by ingestion or inhalation .

  6. 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.

  7. 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 ...

  8. Uncertainty quantification - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_quantification

    Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known.

  9. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables ⁡ (+) = ⁡ + ⁡ + ⁡ (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...