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Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
Uncertainty propagation is the quantification of uncertainties in system output(s) propagated from uncertain inputs. It focuses on the influence on the outputs from the parametric variability listed in the sources of uncertainty. The targets of uncertainty propagation analysis can be:
We compare this to another classifier which predicts the first three as being dogs as 0.95, 0.98, 0.02, and the last three being cats as 0.99, 0.96,0.96. The NLPD for this classifier is 4.08. The first classifier only guessed half correctly, so did worse on a traditional measure of accuracy (compared to 5/6 for the second classifier).
(1) The Type I bias equations 1.1 and 1.2 are not affected by the sample size n. (2) Eq(1.4) is a re-arrangement of the second term in Eq(1.3). (3) The Type II bias and the variance and standard deviation all decrease with increasing sample size, and they also decrease, for a given sample size, when x's standard deviation σ becomes small ...
Software of unknown pedigree (SOUP) is software that was developed with a unknown process or methodology, or which has unknown or no safety-related properties. [1] In the medical device development standard IEC 62304, SOUP expands to software of unknown provenance, and in some contexts uncertain is used instead of unknown, but any combination of unknown/uncertain and provenance/pedigree refer ...
If the perturbation required is small, on the order of the uncertainty in the input data, then the results are in some sense as accurate as the data "deserves". The algorithm is then defined as backward stable .
In physical experiments uncertainty analysis, or experimental uncertainty assessment, deals with assessing the uncertainty in a measurement.An experiment designed to determine an effect, demonstrate a law, or estimate the numerical value of a physical variable will be affected by errors due to instrumentation, methodology, presence of confounding effects and so on.
For an approximately normal data set, the values within one standard deviation of the mean account for about 68% of the set; while within two standard deviations account for about 95%; and within three standard deviations account for about 99.7%.