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  2. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    Should the cholesterol fall from 5.4 to 4.1 to 3.7, there is a clear linear trend. The same principle may be applied to the effects of allele/ genotype frequency , where it could be argued that a single-nucleotide polymorphism in nucleotides XX, XY, YY are in fact a trend of no Y's, one Y, and then two Y's.

  3. Trend analysis - Wikipedia

    en.wikipedia.org/wiki/Trend_analysis

    If the trend can be assumed to be linear, trend analysis can be undertaken within a formal regression analysis, as described in Trend estimation. If the trends have other shapes than linear, trend testing can be done by non-parametric methods, e.g. Mann-Kendall test, which is a version of Kendall rank correlation coefficient.

  4. Jonckheere's trend test - Wikipedia

    en.wikipedia.org/wiki/Jonckheere's_Trend_Test

    In statistics, the Jonckheere trend test [1] (sometimes called the Jonckheere–Terpstra [2] test) is a test for an ordered alternative hypothesis within an independent samples (between-participants) design.

  5. Decomposition of time series - Wikipedia

    en.wikipedia.org/wiki/Decomposition_of_time_series

    The trend-cycle component can just be referred to as the "trend" component, even though it may contain cyclical behavior. [3] For example, a seasonal decomposition of time series by Loess (STL) [ 4 ] plot decomposes a time series into seasonal, trend and irregular components using loess and plots the components separately, whereby the cyclical ...

  6. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    If the means are not known at the time of calculation, it may be more efficient to use the expanded version of the ^ ^ equations. These expanded equations may be derived from the more general polynomial regression equations [ 7 ] [ 8 ] by defining the regression polynomial to be of order 1, as follows.

  7. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    Linear regression was the first type of regression analysis to be studied rigorously, and to be used extensively in practical applications. [4] This is because models which depend linearly on their unknown parameters are easier to fit than models which are non-linearly related to their parameters and because the statistical properties of the ...

  8. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    Smoothed analysis — measuring the expected performance of algorithms under slight random perturbations of worst-case inputs; Symbolic-numeric computation — combination of symbolic and numeric methods; Cultural and historical aspects: History of numerical solution of differential equations using computers

  9. Confidence and prediction bands - Wikipedia

    en.wikipedia.org/wiki/Confidence_and_prediction...

    Confidence bands can be constructed around estimates of the empirical distribution function.Simple theory allows the construction of point-wise confidence intervals, but it is also possible to construct a simultaneous confidence band for the cumulative distribution function as a whole by inverting the Kolmogorov-Smirnov test, or by using non-parametric likelihood methods.