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  2. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    An example of the first resample might look like this X 1 * = x 2, x 1, x 10, x 10, x 3, x 4, x 6, x 7, x 1, x 9. There are some duplicates since a bootstrap resample comes from sampling with replacement from the data. Also the number of data points in a bootstrap resample is equal to the number of data points in our original observations.

  3. Parametric statistics - Wikipedia

    en.wikipedia.org/wiki/Parametric_statistics

    Parametric statistical methods are used to compute the 2.33 value above, given 99 independent observations from the same normal distribution. A non-parametric estimate of the same thing is the maximum of the first 99 scores. We don't need to assume anything about the distribution of test scores to reason that before we gave the test it was ...

  4. Density estimation - Wikipedia

    en.wikipedia.org/wiki/Density_Estimation

    Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as ...

  5. Cost estimation models - Wikipedia

    en.wikipedia.org/wiki/Cost_estimation_models

    The model then provides as output various resources requirements in cost and time. Some models concentrate only on estimating project costs (often a single monetary value). Little attention has been given to the development of models for estimating the amount of resources needed for the different elements that comprise a project. [1]

  6. Estimation (project management) - Wikipedia

    en.wikipedia.org/wiki/Estimation_(project...

    Analogy based estimation; Compartmentalization (i.e., breakdown of tasks) Cost estimate; Delphi method; Documenting estimation results; Educated assumptions; Estimating each task; Examining historical data; Identifying dependencies; Parametric estimating; Risk assessment; Structured planning; Popular estimation processes for software projects ...

  7. Theil–Sen estimator - Wikipedia

    en.wikipedia.org/wiki/Theil–Sen_estimator

    It has also been called Sen's slope estimator, [1] [2] slope selection, [3] [4] the single median method, [5] the Kendall robust line-fit method, [6] and the Kendall–Theil robust line. [7] It is named after Henri Theil and Pranab K. Sen , who published papers on this method in 1950 and 1968 respectively, [ 8 ] and after Maurice Kendall ...

  8. Rayleigh–Ritz method - Wikipedia

    en.wikipedia.org/wiki/Rayleigh–Ritz_method

    Hence M = [m 1, m 2] and K = [k 1, k 2]. A mode shape is assumed for the system, with two terms, one of which is weighted by a factor B , e.g. Y = [1, 1] + B [1, −1]. Simple harmonic motion theory says that the velocity at the time when deflection is zero, is the angular frequency ω {\displaystyle \omega } times the deflection (y) at time of ...

  9. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    The following techniques of distribution fitting exist: [2] Parametric methods, by which the parameters of the distribution are calculated from the data series. [3] The parametric methods are: Method of moments; Maximum spacing estimation; Method of L-moments [4] Maximum likelihood method [5]

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