Estimation and testing for a Poisson autoregressive model

By Fukang Zhu, Dehui Wang. 2011

56 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3d22c7d4f14a7da2a2f8df0e9cfd50e1951bf6d9

How researchers see this paper

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

In Artificial Intelligence

1. Sangyeol Lee
2. Christian H. Weiβ
3. Jiwon Kang
4. Konstantinos Fokianos
5. W. Barreto‐Souza
6. Miguel de Carvalho
7. A. C. Davison

In Finance

1. Sangyeol Lee
2. Jiwon Kang
3. Konstantinos Fokianos
4. Christian H. Weiβ
5. Fukang Zhu
6. Cathy W. S. Chen
7. Youngmi Lee
8. W. Barreto‐Souza

In Statistics and Probability

1. Sangyeol Lee
2. Jiwon Kang
3. Christian H. Weiβ
4. Konstantinos Fokianos
5. Youngmi Lee
6. W. Barreto‐Souza
7. Cathy W. S. Chen
8. Fukang Zhu

Citations in the corpus

• The INARCH(1) Model for Overdispersed Time Series of Counts (2010, background): “it is also irreducible and aperiodic and hence ergodic (Zhu and Wang, 2009); also see Fokianos et al.”
• Some recent progress in count time series (2011, background): “When a =0, then model (4) is recovered, see also Zhu and Whang 35 .”
• Parameter Change Test for Poisson Autoregressive Models (2014, methodology): “Then, an alternative approach to modelling overdispersed count data is to employ integer-valued GARCH (INGARCH) models (cf. Ferland et al., 2006): see also Zhu & Wang (2011).”