autoGPoMoSearch | R Documentation |
This algorithm aims to get an ensemble of possible
models which integrability will be tested later with function
autoGPoMoTest
. By default, all the terms are considered
available (Some of the terms can be excluded intentionally
using the option filterReg
).
The maximum size of the equation depends on the model dimension
nVar
, and on the maximum polynomial degree dMax
.
The algorithm removes polynomial terms one by one using a
leave-one-out method.
autoGPoMoSearch(
data,
dt,
nVar,
dMax,
dMin = 0,
weight = NULL,
show = 0,
underSamp = NULL,
filterReg = NULL
)
data |
Input Time series: Each column is one time series that corresponds to one variable. |
dt |
Time sampling of the input series. |
nVar |
Number of variables considered in the polynomial formulation. |
dMax |
Maximum degree of the polynomial formulation. |
dMin |
The minimum negative degree of the polynomial formulation (0 by default). |
weight |
A vector providing the binary weighting function of the input data series (0 or 1). By default, all the values are set to 1. |
show |
Provide (2) or not (0-1) visual output during the running process. |
underSamp |
Number of points used for undersampling the data.
For |
filterReg |
A vector that specifies the template for
the equation structure (for one single equation).
The convention defined by |
A list of two matrices:
$filtMemo
describes the selected terms
(1 if the term is used, 0 if not)
$KMemo
provides the corresponding coefficients
Sylvain Mangiarotti, Flavie Le Jean
autoGPoMoTest
, gPoMo
,
findAllSets
, poLabs
# Load data
data('RosYco')
# Search for potential models
filt = autoGPoMoSearch(RosYco[,2], nVar = 3, dMax = 2,
dt = 1/125, show = 1)
# As an example, the equations of the fourth line has the following terms:
poLabs(nVar = 3, dMax = 2)[filt$filtMemo[5,] != 0]
# which coefficients correspond to
cbind(filt$KMemo[5,], poLabs(nVar = 3, dMax = 2))[filt$filtMemo[5,] != 0,]
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