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For example, a logistic regression method cannot efficiently handle all variables under consideration.
For example, a logistic regression model for Hamilton, Canada, shows that a 4%% increase in job accessibility would increase transit by 0.2 0.5 % [11].
Here c A,B is a combination function for the values ( upomega_{{C_{1},B}}, ldots,upomega_{{C_{k},B}} ); for example, a logistic sum function or a scaled sum function with scale factor the number k of other persons connected to B. Note that the latter combination function only takes into account the average strengths of the connections, not the total number of them.
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For example, if a logistic regression model provided two or three decimal accuracy for the relevant probabilities, then it could be that this is sufficient accuracy but this depends on the application as sometimes greater accuracy may be required.
For example, in a logistic regression model a product term is estimated as departure from multiplicativity of odds ratios.
We present the example of a logistic and a Lorenz chaotic dynamical system as well as an adaptation of our technique in order to show empirically the robustness of the thresholding method in presence of leptokurtic noise.
An example of a logistic issue is the difficulty in planning a meeting with a participant with sufficient time to administer all the tests and questionnaires.
Firstly, the form of the risk model (for example, logistic or Cox regression for binary and survival data, respectively) is specified using all candidate predictors.
[19] One prominent example of a misinterpretation of a logistic regression coefficient is discussed in the following letter to the editor.
Formal analysis, for example using logistic regression with 'missingness' as a response, may also be appropriate and aid interpretation.
We present an example based on logistic map.
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