In collaboration with Alexander V . Markov he has demonstrated that a similar mathematical model can be developed to describe the logistic models ( traditionally used in population biology and extensively applied to fossil biodiversity as well ).
22.
Wilkinson cited Forrester s ( 1961 ) models of industrial dynamics and Balderston and Hoggat ( 1962 ) models of market processes as fundamental frameworks for following logistic models developed by Bowersox ( 1972 ) and his colleagues.
23.
No need to get in to full-fledged weather prediction-even the simple logistic model will display deterministic chaos ( remember, biology was the other key historical science that motivated chaos theory as a discipline ).
24.
That is to say, if we form a logistic model from such data, if the model is correct in the general population, the \ beta _ j parameters are all correct except for \ beta _ 0.
25.
Many mineral resources have exhibited logistic Hubbert-type production trends in the past, but have transitioned to exponential growth during the last 10 15 years, precluding reliable estimates of reserves from within the framework of the logistic model.
26.
The logistic model including the caffeine ^ 2 term indicates that the quadratic caffeine ^ 2 term is significant ( p = 0.003 ) while the linear caffeine term is not significant ( p = 0.21 ).
27.
The logistic model suggests that the highest proportion of A scores will occur in volunteers who consume zero mg caffeine, when in fact the highest proportion of A scores occurs in volunteer consuming in the range of 100 to 150 mg.
28.
In collaboration with Andrey Korotayev he has demonstrated that a rather simple mathematical model can be developed to describe in a rather accurate way the logistic models ( traditionally used in population biology and extensively applied to fossil biodiversity as well ).
29.
This expression of a Markov field as a logistic model is only possible if all clique factors are non-zero, " i . e . " if none of the elements of \ mathcal { X } are assigned a probability of 0.
30.
Logistic model trees are based on the earlier idea of a model tree : a decision tree that has linear regression models at its leaves to provide a piecewise linear regression model ( where ordinary decision trees with constants at their leaves would produce a piecewise constant model ).
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