Sentence examples for models are inappropriate from inspiring English sources

Having an assumption of the equality of the distributional mean and variance, Poisson models are inappropriate for many count-modeling situations.

Our results suggest that conditional independence models are inappropriate as a general model for network evolution and can lead to distorted substantive findings on structural network effects, such as transitivity.

However, experimental data again showed better agreement with the pseudo-second-order kinetic model where the R 2 values obtained for other three kinetics models are less than 0.9, and the majority of the data do not fall on a straight line, indicating that these models are inappropriate.

However, these models are inappropriate for experiments such as RNAi or pharmacological screens.

Thus, these models are inappropriate for capturing the likely localized nature of the residual spatial autocorrelation, which may contain sub-region of spatial smoothness separated by step changes.

Since LOT makes measurements over length scales of less than a few millimeters, close to the scattering length of typical tissue, diffusion models are inappropriate.

This results in compliance with previous experimental results and so is ultimately proposed as a means of predicting time to crack initiation when the use of more advanced, computationally intensive FE models is inappropriate.

As we could not assume monthly counts of deaths to be normally distributed, simple linear regression models were inappropriate.

Standard statistical tests, e.g. regressing phenotype on allele count in a linear model, are inappropriate for population based WGA in structured populations because they either result in an inflated proportion of spurious marker - phenotype associations or mask true associations (e.g.[ 39, 40]), even with modest levels of population stratification and/or admixture.

For manufacturing processes where no satisfactory analytical model exists, or where a low-order empirical polynomial model is inappropriate, neural networks offer a good alternative predictive modeling approach.

In New York City, however, a consensus has formed among charity and relief groups that such a model is inappropriate for a disaster of this magnitude.