Robust estimation for binomial conditionally nonlinear autoregressive time series based on multivariate conditional frequencies
DOI10.1016/j.jmva.2021.104777zbMath1470.62131OpenAlexW3169490264MaRDI QIDQ2048121
Valeriy A. Voloshko, Yuriy S. Kharin
Publication date: 5 August 2021
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2021.104777
robustnessparameter estimationsensitivity analysisinnovation outliersdiscrete-valued time seriesmultivariate conditional frequencies
Asymptotic properties of parametric estimators (62F12) Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35) Markov processes: estimation; hidden Markov models (62M05)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On binary and categorical time series models with feedback
- Discrete time series, processes, and applications in finance.
- Log-linear Poisson autoregression
- Robust multivariate Bayesian forecasting under functional distortions in the \(\chi^2\)-metric
- Time series of count data: Modeling, estimation and diagnostics
- An approach to asymptotic robustness analysis of sequential tests for composite parametric hypotheses
- Robust regressive forecasting under functional distortions in a model
- Statistical estimation of parameters for binary conditionally nonlinear autoregressive time series
- Semibinomial conditionally nonlinear autoregressive models of discrete random sequences: probabilistic properties and statistical parameter estimation
- Bernoulli vector autoregressive model
- Robustness in Statistical Forecasting
- STATIONARY DISCRETE AUTOREGRESSIVE-MOVING AVERAGE TIME SERIES GENERATED BY MIXTURES
- Innovational Outliers in INAR(1) Models
- Statistical Methods in Markov Chains
- An integer-valued pth-order autoregressive structure (INAR(p)) process
- A New Class of Autoregressive Models for Time Series of Binomial Counts
- Some ARMA models for dependent sequences of poisson counts
- An Introduction to Discrete‐Valued Time Series
- Estimation and Modelling Repeated Patterns in High Order Markov Chains with the Mixture Transition Distribution Model
- Interventions in log-linear Poisson autoregression
- Statistical analysis of conditionally binomial nonlinear regression time series with discrete regressors
- Interventions in INGARCH processes
- A Markov chain of order s with r partial connections and statistical inference on its parameters
- Retrospective Bayesian outlier detection in INGARCH series