Description Usage Arguments Details Value Note Author(s) References See Also Examples
Given an object of type quarry
, the function computes the probabilities
of each level of interaction (low, medium, high and very high) using a Logit
discrete choice model.
1 2 | ## S3 method for class 'quarry'
compute.dc(x, ...)
|
x |
An object of type quarry. |
... |
Further arguments passed to or from other methods. |
The model parameters have been estimated with BIOGEME and has an adjusted ρ-square of 0.609. The model is fully detailed in the paper "Interaction prediction between groundwater and quarry extension using discrete choice models and artificial neural networks" (Barthelemy et al., 2016).
A list whose elements are:
p.low |
The probability of a low interaction level. |
p.medium |
The probability of a medium interaction level. |
p.high |
The probability of a high interaction level. |
p.very.high |
The probability of a very high interaciton level. |
In order to use the function, the quarry must have been constructed with the
function quarry
using the default parameters.
Johan Barthelemy.
Maintainer: Johan Barthelemy johan@uow.edu.au.
Barthelemy, J., Carletti, T., Collier L., Hallet, V., Moriame, M., Sartenaer, A. (2016) Interaction prediction between groundwater and quarry extension using discrete choice models and artificial neural networks Environmental Earth Sciences (in press)
Collier, L., Barthelemy, J., Carletti, T., Moriame, M., Sartenaer, A., Hallet, V. (2015) Calculation of an Interaction Index between the Extractive Activity and Groundwater Resources Energy Procedia 76, 412-420
Bierlaire, M. (2003) BIOGEME: a free package for the estimation of discrete choice models. Swiss Transport Research Conference TRANSP-OR-CONF-2006-048
compute.ann
to compute an interaction index
based on an artificial neural network and
compute.interaction
to predict the
interaction between between the quarry and the groundwater using both the
discrete choice-based index and the neural network-based index.
1 2 3 4 5 6 7 | # creating a quarry
q <- quarry(geological.context = 2, hydrogeological.context = 4,
piezometric.context = 1, quarry.position = 4,
production.catchment = 4, quality.catchment = 3)
# computing the interaction index
inter.idx <- compute.dc(q)
|
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