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  2. Mean squared error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_error

    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).

  3. Proofs involving ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Proofs_involving_ordinary...

    Using the Law of iterated expectation this can be written as. Recall that M = I − P where P is the projection onto linear space spanned by columns of matrix X. By properties of a projection matrix, it has p = rank (X) eigenvalues equal to 1, and all other eigenvalues are equal to 0. Trace of a matrix is equal to the sum of its characteristic ...

  4. Minimum mean square error - Wikipedia

    en.wikipedia.org/wiki/Minimum_mean_square_error

    Standard method like Gauss elimination can be used to solve the matrix equation for .A more numerically stable method is provided by QR decomposition method. Since the matrix is a symmetric positive definite matrix, can be solved twice as fast with the Cholesky decomposition, while for large sparse systems conjugate gradient method is more effective.

  5. Mean squared prediction error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_prediction_error

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  6. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Propagation of uncertainty. In statistics, propagation of uncertainty (or propagation of error) is the effect of variables ' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement ...

  7. Bessel's correction - Wikipedia

    en.wikipedia.org/wiki/Bessel's_correction

    Bessel's correction. In statistics, Bessel's correction is the use of n − 1 instead of n in the formula for the sample variance and sample standard deviation, [1] where n is the number of observations in a sample. This method corrects the bias in the estimation of the population variance. It also partially corrects the bias in the estimation ...

  8. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    It is remarkable that the sum of squares of the residuals and the sample mean can be shown to be independent of each other, using, e.g. Basu's theorem.That fact, and the normal and chi-squared distributions given above form the basis of calculations involving the t-statistic:

  9. Cramér–Rao bound - Wikipedia

    en.wikipedia.org/wiki/Cramér–Rao_bound

    In estimation theory and statistics, the Cramér–Rao bound (CRB) relates to estimation of a deterministic (fixed, though unknown) parameter. The result is named in honor of Harald Cramér and C. R. Rao, [1][2][3] but has also been derived independently by Maurice Fréchet, [4] Georges Darmois, [5] and by Alexander Aitken and Harold ...