fit.CInLPN: Marginal and subject-specific predictions on the training...

In bachirtadde/CInLPN: Causal Inference for Latent Processes Network

Marginal and subject-specific predictions on the training data for a CInLPN object

Description

Marginal and subject-specific predictions on the training data for a CInLPN object

Usage

fit.CInLPN(object, newdata, TimeDiscretization = TRUE, MCnr = 10, ...)

Arguments

object	CInLPN object
newdata	dataset
TimeDiscretization	a boolean indicating if the inital time have to be discretized. When setting to FALSE, It allows to avoid discretization when running univarite model during parameter initialization.
MCnr	an integer that gives the number of Monte Carlo iterations
...	optional parameters

Value

list of marginal and subject-specific predictions

bachirtadde/CInLPN documentation built on June 30, 2023, 11:47 a.m.