root-mean-square deviation
root-mean-square error

Next, the root-mean-square deviation from the trend, the fluctuation, is calculated over every window at every time scale:

It is analogous to the 'root-mean-square deviation' in electrical engineering and to the 'radius of gyration'in moments of inertia in mechanical engineering.

It is useful in graphics, cheminformatics to compare molecular structures, and also bioinformatics for comparing protein structures (in particular, see root-mean-square deviation (bioinformatics)).

Three-dimensional superpositions of the three of these domains for which structures are available aligned the C-α atoms with a root-mean-square deviation of 3.2Å or less for approximately 60 residues.

Another method of specifying spectral width is a special case of root-mean-square deviation where the independent variable is wavelength, λ, and f (λ) is a suitable radiometric quantity.

The "SuperPose" web server uses "RMSD" or Root-Mean-Square Deviation as a difference measure to find the optimal pairwise or multiple protein structure superposition.

The most common method of comparing two protein structures uses the root-mean-square deviation (RMSD) metric to measure the mean distance between the corresponding atoms in the two structures after they have been superimposed.

This value is commonly referred to as the normalized root-mean-square deviation or error (NRMSD or NRMSE), and often expressed as a percentage, where lower values indicate less residual variance.

An example of a situation in which a non-trivial progress coordinate might be required is for protein folding: a simple root-mean-square deviation might prove to be non-monotonic in the true reaction coordinate, leading potentially to trapping of the calculation, depending on the algorithm used.

A comparison of the two approaches was carried out by examining mean relative error and root-mean-square error.

Key words: snow water equivalent, kriging with external drift, root-mean-square errors, digital elevation model.

In addition, the KLM can not make a perfect prediction and has a root-mean-square error of 21%.

Quantizers, or analog-to-digital converters, can use lattices to minimise the average root-mean-square error.

This comparison contains a graphical daily analysis, a statistical analysis including the calculation of root-mean-square error, and a comparative performance study.

RMS: Root-Mean-Square error (a type of statistical average)

By the way, the root-mean-square error derived from any model is the standard deviation of the residuals, and the mean of the residuals is always zero.

You’ll also see a calculation called the R.M.S.E., or root-mean-square error, sometimes also called the standard error.

Root-mean-square error of the geopotential height at 500hPa relative to radiosonde observations over North America as a function of lead time from the operational (black) and parallel (red) forecast systems.

I am simply suggesting that viewed at a distance, the models will rarely “fail” (as the headline of Nate’s post has it) in a way that misleads the average person who follows politics and wants to know only who’s the likely winner, but doesn’t care about root-mean-square error.