The time-rescaling theorem and its application to neural spike train data analysis
type: Item
instance of: scholarly article
DOI: 10.1162/08997660252741149
published in: Neural Computation
volume: 14
issue: 2
page(s): 325-346
publication date: 2002-02-01T00:00:00Z
publication date: 2002-07-02T00:00:00Z
author: Emery N. Brown
author: R. Barbieri
author: Valérie Ventura
author: Robert E. Kass
author: Loren M. Frank
zbMATH Open document ID: 0989.62060
Mathematics Subject Classification ID: 62P10
Mathematics Subject Classification ID: 92C20
zbMATH DE Number: 1720073
zbMATH Keywords: time-rescaling theorem
zbMATH Keywords: goodness-of-fit tests
zbMATH Keywords: point process models
zbMATH Keywords: neural spike train models
Wikidata QID: Q32060331
describes a project that uses: R
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1162/08997660252741149
OpenAlex ID: W2110242299
cites work: Maximum likelihood analysis of spike trains of interacting nerve cells
cites work: A spike-train probability model
cites work: Simulation of nonhomogeneous poisson processes by thinning
cites work: On Lewis' simulation method for point processes
DBLP publication ID: journals/neco/BrownBVKF02
title: The time-rescaling theorem and its application to neural spike train data analysis
description: scientific article; zbMATH DE number 1720073