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  2. Bootstrapping (statistics) - Wikipedia

    Bootstrapping is any test or metric that uses random sampling with replacement (e.g. mimicking the sampling process), and falls under the broader class of resampling methods. Bootstrapping assigns measures of accuracy (bias, variance, confidence intervals, prediction error, etc.) to sample estimates.

  3. Resampling (statistics) - Wikipedia

    Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio, correlation coefficient or regression coefficient.

  4. Component Object Model - Wikipedia

    An example of a compound document is a spreadsheet embedded in a Word for Windows document: as changes are made to the spreadsheet within Excel, they appear automatically inside the Word document. In 1991, Microsoft introduced Visual Basic Extensions (VBX) with Visual Basic 1.0.

  5. Programming with Big Data in R - Wikipedia

    Programming with Big Data in R (pbdR) is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical software.

  6. Snippet (programming) - Wikipedia

    Snippet is a programming term for a small region of re-usable source code, machine code, or text. Ordinarily, these are formally defined operative units to incorporate into larger programming modules. Snippet management is a feature of some text editors, program source code editors, IDEs, and related software.

  7. Estimation of covariance matrices - Wikipedia

    The sample covariance matrix (SCM) is an unbiased and efficient estimator of the covariance matrix if the space of covariance matrices is viewed as an extrinsic convex cone in Rp×p; however, measured using the intrinsic geometry of positive-definite matrices, the SCM is a biased and inefficient estimator. In addition, if the random variable ...

  8. Jackknife resampling - Wikipedia

    Statistical method. In statistics, the jackknife is a resampling technique especially useful for variance and bias estimation. The jackknife pre-dates other common resampling methods such as the bootstrap. The jackknife estimator of a parameter is found by systematically leaving out each observation from a dataset and calculating the estimate ...