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State-Space Systems
Linear state-space systems, like ARMA systems, are models for stationary processes, more precisely for the class of stationary processes with...
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An extended Langevinized ensemble Kalman filter for non-Gaussian dynamic systems
State estimation for large-scale non-Gaussian dynamic systems remains an unresolved issue, given nonscalability of the existing particle filter...
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Optimal experimental design for linear time invariant state–space models
The linear time invariant state–space model representation is common to systems from several areas ranging from engineering to biochemistry. We...
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State Space Models
This chapter introduces state space models and provides some motivating examples. Linear Gaussian and non-linear, non-Gaussian models are introduced....
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Dynamic Systems and Control
Dynamic systems are discussed in this chapter. This chapter is different in style in comparison to the other chapters of the book. The idea is to...
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Non-Linear and Non-Gaussian State Space Models
This chapter discusses estimation for non-linear and non-Gaussian state space methods. We start by defining conditionally Gaussian and more general...
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A Bayesian Approach for Data-Driven Dynamic Equation Discovery
Many real-world scientific and engineering processes are governed by complex nonlinear interactions, and differential equations are commonly used to...
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Dynamic Factor Models
In this chapter, we deal with linear dynamic factor models and related topics, such as dynamic principal component analysis (dynamic PCA). The main...
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Bayesian Computations for Reliability Analysis in Dynamic Environments
In this chapter, we consider systems operating under a dynamic environment that causes changes in the failure characteristics of the system. We...
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A Dynamic Occupancy Model for Interacting Species with Two Spatial Scales
Occupancy models have been extended to account for either multiple spatial scales or species interactions in a dynamic setting. However, as...
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Modeling Structural Breaks in Disturbances Precision or Autoregressive Parameter in Dynamic Model: A Bayesian Approach
The focus of this paper is the examination of dynamic models in the presence of structural changes either due to disturbances precision or...
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Variable Universe Fuzzy Control Based on Adaptive Error Integral for Uncertain Nonlinear Systems with Time-Delay
This article deals with variable universe fuzzy control (VUFC) based on adaptive error integral for uncertain nonlinear systems with time delay. A...
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A dynamic causal modeling of the second outbreak of COVID-19 in Italy
While the vaccination campaign against COVID-19 is having its positive impact, we retrospectively analyze the causal impact of some decisions made by...
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Estimation of the Parameters in an Expanding Dynamic Network Model
In this paper, we consider an expanding sparse dynamic network model where the time evolution is governed by a Markovian structure. Transition of the...
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Introduction to State-Space Models
The sequential analysis of state-space models remains to this day the main application of Sequential Monte Carlo. The intent of this Chapter is to...
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Time Series Models
This textbook provides a self-contained presentation of the theory and models of time series analysis. Putting an emphasis on weakly stationary...
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State Space Models of Time Series
Kalman filter presents a theoretical background for various recursive methods in (linear) systems, particularly in (multivariate) time series models....
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Adaptive Likelihood Ratio Scans for the Detection of Space-Time Clusters
This work presents a methodology to detect space-time clusters, based on adaptive likelihood ratios (ALRs), which preserves the martingale structure...
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Bayesian Models for Dynamic Scene Analysis
In this chapter, we discuss Bayesian approaches for foreground object detection and localization in video surveillance applications. Two different...
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Marked Spatial Point Processes: Current State and Extensions to Point Processes on Linear Networks
Within the applications of spatial point processes, it is increasingly becoming common that events are labelled by marks, prompting an exploration...
