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  2. Robust statistics - Wikipedia

    en.wikipedia.org/wiki/Robust_statistics

    Robust statistical methods have been developed for many common problems, such as estimating location, scale, and regression parameters. One motivation is to produce statistical methods that are not unduly affected by outliers .

  3. Robust regression - Wikipedia

    en.wikipedia.org/wiki/Robust_regression

    The two regression lines appear to be very similar (and this is not unusual in a data set of this size). However, the advantage of the robust approach comes to light when the estimates of residual scale are considered. For ordinary least squares, the estimate of scale is 0.420, compared to 0.373 for the robust method.

  4. Robust parameter design - Wikipedia

    en.wikipedia.org/wiki/Robust_parameter_design

    Robust parameter designs use a naming convention similar to that of FFDs. A 2 (m1+m2)-(p1-p2) is a 2-level design where m1 is the number of control factors, m2 is the number of noise factors, p1 is the level of fractionation for control factors, and p2 is the level of fractionation for noise factors. Effect sparsity.

  5. Robustification - Wikipedia

    en.wikipedia.org/wiki/Robustification

    Robustification is a form of optimisation whereby a system is made less sensitive to the effects of random variability, or noise, that is present in that system's input variables and parameters. The process is typically associated with engineering systems , but the process can also be applied to a political policy , a business strategy or any ...

  6. Heteroskedasticity-consistent standard errors - Wikipedia

    en.wikipedia.org/wiki/Heteroskedasticity...

    RATS: robusterrors option is available in many of the regression and optimization commands (linreg, nlls, etc.). Stata: robust option applicable in many pseudo-likelihood based procedures. [19] Gretl: the option --robust to several estimation commands (such as ols) in the context of a cross-sectional dataset produces robust standard errors. [20]

  7. Blocking (statistics) - Wikipedia

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

    By running a different design for each replicate, where a different effect gets confounded each time, the interaction effects are partially confounded instead of completely sacrificing one single effect. [4] Replication enhances the reliability of results and allows for a more robust assessment of treatment effects. [12]

  8. The Surprising Place People Are Getting Botox—and What ...

    www.aol.com/surprising-place-people-getting...

    Research on high heel pain found that women experience a progressive increase in foot pain after 3.5 hours, especially when wearing three-inch heels or higher. Pain mainly centers on the heel bone ...

  9. Robust measures of scale - Wikipedia

    en.wikipedia.org/wiki/Robust_measures_of_scale

    Robust measures of scale can be used as estimators of properties of the population, either for parameter estimation or as estimators of their own expected value.. For example, robust estimators of scale are used to estimate the population standard deviation, generally by multiplying by a scale factor to make it an unbiased consistent estimator; see scale parameter: estimation.