An EM-Based Viterbi Approximation Algorithm for Mixed-State Latent Factor Models
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Publication:3532764
DOI10.1080/03610920802040415zbMath1147.62368OpenAlexW2093697016MaRDI QIDQ3532764
Christian Lavergne, Mohamed Saidane
Publication date: 28 October 2008
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610920802040415
Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05)
Cites Work
- Unnamed Item
- Unnamed Item
- Analysis of time series subject to changes in regime
- Estimating the dimension of a model
- Dynamic linear models with Markov-switching
- Autoregressive conditional heteroskedasticity and changes in regime
- Generalized autoregressive conditional heteroscedasticity
- Conditionally heteroscedastic factorial HMMs for time series in finance
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Volatility and Links between National Stock Markets
- Quadratic ARCH Models
- An analysis of variance test for normality (complete samples)
- Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
- Identification, estimation and testing of conditionally heteroskedastic factor models
- A new look at the statistical model identification