Sentence examples for models typically have from inspiring English sources

The quantitative models typically have their origins in academia and often the physical sciences.

Godfrey-Smith (2001) makes the observation that the censored and uncensored test models typically have different complexity.

These models typically have many factors of different character, such as operational, design-based, technological, and economics-based.

Variational correspondence models typically have two terms, the first one being a data term (e.g., based on the grey level constancy), while the second one is a regularisation term used to make the solution smooth.

Public models and simulations are available to anyone who logs on to VCell, as specified by their creators; the number of simulations is larger than the number of models, because models typically have several simulations associated with them.

Constructing the matrix and the right-hand side in step (1.4) is done with linear complexity (O(n^{1})), but the constant factor of the complexity function is of order 103-105, since the industrial semiconductor models typically have numerous nonlinear equations to evaluate.

Earlier models typically had 14 channels -- users set their radios to the same channel before going their separate ways -- but companies have added channels to newer radios as well as codes within each channel to spread out the traffic.

The null model had a range of within country standard deviations from 0.05 to 0.18, whereas the more complex models typically had a range about half this, between approximately 0.07 and 0.14.

SA models obtained by MAP adaptation require the data storage as much as a speaker-independent (SI) model needs, and the SI model typically has billions of parameters.

Although it is true in general that the more descriptors used to build a model, the better the model predicts the training set data, such a model typically has very poor predictive ability when presented with unseen test data, a phenomenon known as overfitting [2].

This tumor model typically has a 160-day lapse between tumor engraftment and full tumor growth (data not shown).