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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.
Relative change. In any quantitative science, the terms relative change and relative difference are used to compare two quantities while taking into account the "sizes" of the things being compared, i.e. dividing by a standard or reference or starting value. [1] The comparison is expressed as a ratio and is a unitless number.
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).
In bioinformatics, the root mean square deviation of atomic positions is the measure of the average distance between the atoms of superimposed proteins. In structure based drug design, the RMSD is a measure of the difference between a crystal conformation of the ligand conformation and a docking prediction.
The value of this calculation is summed for every fitted point t and divided again by the number of fitted points n. The earliest reference to similar formula appears to be Armstrong (1985, p. 348) where it is called "adjusted MAPE " and is defined without the absolute values in denominator.
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Measurement uncertainty. In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a measured quantity. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation.