Bayesian predictions of low count time series

By Brendan McCabe, Gael M. Martin. 2005

111 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/95beda0abf67a7404da635a7efdad662e7f083c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

Citations in the corpus

Efficient probabilistic forecasts for counts (2011, background): “…by, among others, Du and Li (1991), Dion et al. (1995), Latour (1998), Ispany et al. (2003), Freeland and McCabe (2004), Jung et al. (2005), McCabe and Martin (2005), Silva and Oliveira (2005), Jung and Tremayne (2006), Zhu and Joe (2006), Neal and Subba Rao (2007), Bu and McCabe (2008),…”
Integer-Valued Self-Exciting Threshold Autoregressive Processes (2012, background): “…series of counts has become an important area of research in the last two decades partially because of its wide applicability to social science (McCabe and Martin, 2005), queueing systems (Ahn et al., 2000), experimental biology (Zhou and Basawa, 2005), environmental processes (Thyregod et…”
MCMC for Integer‐Valued ARMA processes (2007, unknown): “inference (see, e.g. Freeland and McCabe, 2004; McCabe and Martin, 2005), although, recently, Jung and Tremayne (2006) have considered an INAR(2) process.”
25 Years of IIF Time Series Forecasting: A Selective Review (2005, methodology): “McCabe & Martin (2005) further extended these ideas by presenting a Bayesian methodology for forecasting from the INAR class of models.”
25 years of time series forecasting (2006, methodology): “Note that Armstrong and Collopy (1992) referred to RelMAE as CumRAE and that RelRMSE is also known as Theil’s U statistic (Theil, 1966, Chapter 2), and is sometimes called U2.”
Model Selection, Estimation and Forecasting in INAR(p) Models: (2008, background): “McCabe and Martin (2005) explored the issue of coherent forecasting with count data models under the Bayesian framework but they too are only concerned with rst-order case.”
Efficient Estimation of Autoregression Parameters and Innovation Distributions forSemiparametric Integer-Valued AR(p) Models (Revision of DP 2007-23) (2008, unknown): “Gouriéroux, C. and J. Jasiak (2004).”