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  2. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    For correlated random variables the sample variance needs to be computed according to the Markov chain central limit theorem.. Independent and identically distributed random variables with random sample size

  3. Heteroskedasticity-consistent standard errors - Wikipedia

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

    The topic of heteroskedasticity-consistent ( HC) standard errors arises in statistics and econometrics in the context of linear regression and time series analysis. These are also known as heteroskedasticity-robust standard errors (or simply robust standard errors ), Eicker–Huber–White standard errors (also Huber–White standard errors or ...

  4. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    where ¯ represents the errors, represents the sample standard deviation for a sample of size n, and unknown σ, and the denominator term / accounts for the standard deviation of the errors according to:

  5. Clustered standard errors - Wikipedia

    en.wikipedia.org/wiki/Clustered_standard_errors

    Huber-White standard errors assume is diagonal but that the diagonal value varies, while other types of standard errors (e.g. Newey–West, Moulton SEs, Conley spatial SEs) make other restrictions on the form of this matrix to reduce the number of parameters that the practitioner needs to estimate.

  6. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    where represents the standard deviation of the function , represents the standard deviation of , represents the standard deviation of , and so forth.. It is important to note that this formula is based on the linear characteristics of the gradient of and therefore it is a good estimation for the standard deviation of as long as ,,, … are small enough.

  7. Mean squared error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_error

    Definition and basic properties. The MSE either assesses the quality of a predictor (i.e., a function mapping arbitrary inputs to a sample of values of some random variable), or of an estimator (i.e., a mathematical function mapping a sample of data to an estimate of a parameter of the population from which the data is sampled).

  8. Residual sum of squares - Wikipedia

    en.wikipedia.org/wiki/Residual_sum_of_squares

    In statistics, the residual sum of squares ( RSS ), also known as the sum of squared residuals ( SSR) or the sum of squared estimate of errors ( SSE ), is the sum of the squares of residuals (deviations predicted from actual empirical values of data). It is a measure of the discrepancy between the data and an estimation model, such as a linear ...

  9. Error analysis (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Error_analysis_(mathematics)

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