Chemical model determination experimental error

The minimum value of /Jdf/v required for a reliable model depends on the quality of the determination of the data to be correlated. The smaller the experimental error in the data, the smaller the value of /Jdf/v required for dependable results. Experience indicates that in the case of chemical reactivity data /Jdf/v should be not less than 3. For bioactivity studies /Jdf/v depends heavily on the type of data for rate and equilibrium constants obtained from enzyme kinetics a value of not less than 3 is reasonable while for toxicity studies on mammals at least 7 is required. 

Further work ought to include creation of simulated ambient data sets from a simple source model with known source compositions and contributions perturbed by typical experimental error. The multivariate models should be applied to these data sets, as did Watson (9) for the chemical mass balance, to determine the extent to which the models can apportion source contributions under various conditions. 

Experimentally determined electron density maps are never perfect because of defects in the data and phases, and as a consequence even the best of models will have errors in atomic positions, errors in dihedral angles, improper rotomers for side chains, or unacceptable contacts between atoms or chemical groups. When the quality of an electron density map is marginal or poor, serious errors in the model may occur, or the model may be fundamentally wrong. Even when the electron density map is good, and the model for most practical purposes correct, errors remain. The initial model for a protein will, in general, have rms errors in atomic positions of 1A or more, and an R factor computed from the model (with the exception perhaps of models obtained from molecular replacement) on the order of 0.50, an often discouraging result. 

How accurately systems with various numbers of atoms can be simulated depends therefore on the accuracy of the chosen values for chemical potential. From a numerical point of view, values should be chosen that maximise favour le cancellation of systematic errors. From the modelling point of view, we seek to link p reliably to physical reality. In the next sections we assess a number of jqjproaches to determining p and relating it to experimental conditions. 

Economics in process control, 3, 10-11, 15, 26, 532-34 Environmental regulations, 3 Equal-percentage valve, 254, 255 Equations of state, 57 Equilibria, 56, 78 chemical, 56 phase, 56-57, 71, 75, 78 Error criteria (see Time integral criteria) Euler s identities, 131-32, 149 Experimental modeling, 45, 656 frequency response techniques, 668 process identification, 657-62 time constant determination, 228, 232 Exponential function, 130 approximations, 215-16 Laplace transform, 130 z-transform, 592... 

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