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  2. Mean squared error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_error

    The MSE can be written as the sum of the variance of the estimator and the squared bias of the estimator, providing a useful way to calculate the MSE and implying that in the case of unbiased estimators, the MSE and variance are equivalent. [5]

  3. Mean squared prediction error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_prediction_error

    When the model has been estimated over all available data with none held back, the MSPE of the model over the entire population of mostly unobserved data can be estimated as follows.

  4. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

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  5. Peak signal-to-noise ratio - Wikipedia

    en.wikipedia.org/wiki/Peak_signal-to-noise_ratio

    For color images with three RGB values per pixel, the definition of PSNR is the same except that the MSE is the sum over all squared value differences (now for each color, i.e. three times as many differences as in a monochrome image) divided by image size and by three.

  6. Minimum-variance unbiased estimator - Wikipedia

    en.wikipedia.org/wiki/Minimum-variance_unbiased...

    In statistics a minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter.

  7. How to Calculate a Business Owner’s Salary - AOL

    www.aol.com/finance/calculate-business-owner...

    Calculate your net income. Calculating your net income ensures your business can cover expenses before calculating your own pay. This step is crucial to avoid debt or even bankruptcy. First ...

  8. 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.

  9. Mean signed deviation - Wikipedia

    en.wikipedia.org/wiki/Mean_signed_deviation

    The mean signed difference is derived from a set of n pairs, (^,), where ^ is an estimate of the parameter in a case where it is known that =.In many applications, all the quantities will share a common value.