JSTOR Daily

UNIFORM CONVERGENCE OVER TIME OF A NESTED PARTICLE FILTERING SCHEME FOR RECURSIVE PARAMETER ESTIMATION IN STATE-SPACE MARKOV MODELS

We analyse the performance of a recursive Monte Carlo method for the Bayesian estimation of the static parameters of a discrete-time state-space Markov model. The algorithm employs two layers of ...
Nature

Kalman Filtering and State Estimation in Stochastic Systems

Kalman filtering remains a cornerstone of state estimation in stochastic systems, enabling the real‐time integration of noisy measurements into dynamic system models. Originally developed for linear ...
Risk

Recursive estimation of the exponentially weighted moving average model

The exponentially weighted moving average (EWMA) model is a particular modeling scheme, supported by RiskMetrics, that is capable of forecasting the current level of volatility of financial time ...
Risk

Recursive estimation of the exponentially weighted moving average model

The exponentially weighted moving average (EWMA) model is a particular modeling scheme, supported by RiskMetrics, that is capable of forecasting the current level of volatility of financial time ...