FitNonperiodicModel: Fit nonperiodic model

In dpwynne/mmnst: Multiscale Modeling of Neural Spike Trains

Fit nonperiodic model

Description

Fits the nonperiodic multiscale model.

Usage

FitNonperiodicModel(spikes, setup.pars, terminal.points, ct)

Arguments

spikes	a list of spike trains.
setup.pars	a list of additional parameters for the likelihood function, computed by the SetupLikelihoods() function.
terminal.points	a numeric vector containing the time points at which c(t) changes.
ct	a numeric vector containing the estimated piecewise constant intensity function c(t). The length of ct should be a whole number power of 2.

Value

A list of length 3 is returned. The first item in the list is a matrix whose rows each contain the MLEs of eta for a single spike train (this should be 0). The second item in the list is a matrix whose rows each contain the MLEs of gamma for a single spike train (this should also be 0). The third item in the list is a matrix whose rows each contain the AIC, AICc, BIC, and log-likelihood for the model for a single spike train.

References

Ramezan, R., Marriott, P., and Chenouri, S. (2014), Statistics in Medicine, 33(2), 238-256. doi: 10.1002/sim.5923.

dpwynne/mmnst documentation built on Feb. 22, 2025, 8:44 a.m.