Asymptotic inference for stochastic processes

DOI10.1016/0304-4149(80)90010-1zbMath0442.62065OpenAlexW2050055247MaRDI QIDQ1143730

Ishwar V. Basawa, B. L. S. Prakasa Rao

Publication date: 1980

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(80)90010-1

zbMATH Keywords

surveylikelihood ratiomaximum likelihoodscore testsdensity estimationergodicnon- ergodic

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09) Point estimation (62F10) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Diffusion processes (60J60) Sequential statistical analysis (62L10) Non-Markovian processes: hypothesis testing (62M07) Asymptotic properties of parametric tests (62F05) Sequential estimation (62L12) Markov processes: hypothesis testing (62M02)

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Parameter estimation in continuous-time stochastic processes, Bayesian analysis for finite Markov chains, Stochastic Gradient Descent in Continuous Time, Stochastic Gradient Descent in Continuous Time: A Central Limit Theorem, Martingale Estimating Functions for Stochastic Processes: A Review Toward a Unifying Tool, The robust focused information criterion for strong mixing stochastic processes with \(\mathscr{L}^2\)-differentiable parametric densities, Convergence results for continuous-time adaptive stochastic filtering algorithms, A note on statistical inference for a class of diffusions and approximate diffusions, A note on asymptotic inference in a class of non-stationary processes, Recursive identification in continuous-time stochastic processes, Estimation of the drift for diffusion process

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