Change-Point Analysis of Neuron Spike Train Data

DOI10.2307/2534000zbMath1058.62576OpenAlexW4300696256WikidataQ32067858 ScholiaQ32067858MaRDI QIDQ4665945

Patrick Bélisle, Lawrence Joseph, Roxane du Berger, David B. Wolfson, K. Brenda MacGibbon

Publication date: 11 April 2005

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/05f05af85b6c10b32ba968ee7c979221475e805f

zbMATH Keywords

longitudinal dataautoregressive time seriesGibbs samplerBayesian inferencechange-pointMarkov-chain Monte Carlointeger-valued time seriesinteger-valued autoregressive model

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Neural biology (92C20)

Related Items (10)

ON EXACT INFERENCE FOR CHANGE IN A POISSON SEQUENCE ⋮ Efficient Estimation of Auto-Regression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models ⋮ The asymptotic structure of nearly unstable non-negative integer-valued AR(1) models ⋮ Bayesian multiple change-point estimation with annealing stochastic approximation Monte Carlo ⋮ Using labeled data to evaluate change detectors in a multivariate streaming environment ⋮ Cusum techniques for timeslot sequences with applications to network surveillance ⋮ Semi-parametric dynamic time series modelling with applications to detecting neural dynamics ⋮ Generalized RCINAR(p) Process with Signed Thinning Operator ⋮ Change-point problems: bibliography and review ⋮ Inference for Random Coefficient INAR(1) Process Based on Frequency Domain Analysis

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