Description Usage Arguments Details Value See Also Examples
View source: R/gpsimLinearFunctions.R
creates a model for single input motifs with Gaussian processes.
1 2 3 4 | gpsimCreate(Ngenes, Ntf, times, y,
yvar, options, genes=NULL, annotation=NULL)
gpdisimCreate(Ngenes, Ntf, times, y,
yvar, options, genes=NULL, annotation=NULL)
|
Ngenes |
number of genes to be modelled in the system. |
Ntf |
number of proteins to be modelled in the system. |
times |
the time points where the data is to be modelled. |
y |
the values of each gene at the different time points. |
yvar |
the variances of each gene at the different time points. |
options |
options structure (optional). |
genes |
names of the probes the model is for |
annotation |
(optional) annotation for the probe names |
These functions are meant to be used through GPLearn
.
model |
model structure containing default parameterisation. |
modelExtractParam, modelOptimise, GPLearn
.
1 | ## missing, see GPLearn
|
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