modelExpandParam: Update a model structure with new parameters or update the...

In ahonkela/tigre: Transcription factor Inference through Gaussian process Reconstruction of Expression

Description

Update a model structure or component with new parameters, or update the posterior processes.

Usage

  modelExpandParam(model, params)
  modelUpdateProcesses(model, predt=NULL)

Arguments

model	the model structure to be updated.
params	vector of parameters.
predt	(optional) a vector of times to infer the posterior at. By default this is 100 points spanning the time range of the data.

Details

model <- modelExpandParam(model, param) returns a model structure filled with the parameters in the given vector. This is used as a helper function to enable parameters to be optimised in, for example, the optimisation functions.

model <- modelUpdateProcesses(model) updates posterior processes of the given model.

Value

model

updated model structure.

See Also

GPLearn, modelExtractParam

Examples

## Not run: 
  # Learn the model
  model <- GPLearn(...)
  params <- modelExtractParam(model, only.values=TRUE)
  params[1] <- 0
  new_model <- modelExpandParam(model, params)
  new_model <- modelUpdateProcesses(new_model)

## End(Not run)

ahonkela/tigre documentation built on Aug. 6, 2021, 12:08 p.m.