The phrase "derivative measures" is correct and usable in written English.
It can be used in contexts related to mathematics, finance, or statistics where measures derived from other measures are discussed.
Example: "The study focused on the derivative measures of economic performance to assess the impact of policy changes."
Alternatives: "derived metrics" or "secondary measures."
The shape derivative measures the sensitivity of boundary perturbations while the topological derivative measures the sensitivity of creating a small hole in the interior domain.
The topological derivative measures the sensitivity of a given shape functional with respect to an infinitesimal singular domain perturbation.
The derivative measures the instantaneous rate of change of the function, as distinct from its average rate of change, and is defined as the limit of the average rate of change in the function as the length of the interval on which the average is computed tends to zero.
This finding raises questions regarding both the direct use of the ΔF/F measure, and regarding the use of derivative measures such as area of activation.
However, because network structure – particularly evolving network structure – is difficult to represent concisely, derivative measures are often employed [ 19].
Changes in matrix mineral density is expected to cause an increase in BMD, irrespective of bone volume changes, and result in an overestimation of BV/TV and propagate error to the derivative measures of Tb.Th and Tb.Sp, confounding any actual therapy-related effect on trabecular bone volume and structure.
Following [ 13], we implement mean (MEAN), variance (VAR), and mean derivative (DERIV) measures, which have proved to be valid in cancer/norm discrimination tasks.
While compartmental models indices directly quantify the fraction of different cell compartments in each voxel, EAP-derived indices are only a derivative measure and the effect of the different microstructural configurations on the indices is still unclear.
We incorporated three different descriptors (LBP, local contrast measure, and local directional derivative measure) with three spatial resolutions and evaluated our approach using two comprehensive texture databases.
Smooth supersaturated models are interpolation models in which the underlying model size, and typically the degree, is higher than would normally be used in statistics, but where the extra degrees of freedom are used to make the model smooth using a standard second derivative measure of smoothness.
This is the derivative measure of entropy, known as perplexity (PP) [17].
