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Noise covariance matrices in state‐space models: A survey and comparison of estimation methods—Part I

International journal of adaptive control and signal processing, 2017-11, Vol.31 (11), p.1505-1543

2017

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Latent Gaussian Count Time Series

Journal of the American Statistical Association, 2023-01, Vol.118 (541), p.596-606

2023

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An Invitation to Sequential Monte Carlo Samplers

Journal of the American Statistical Association, 2022-09, Vol.117 (539), p.1587-1600

2022

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Macroeconomics and the reality of mixed frequency data

Journal of econometrics, 2016-08, Vol.193 (2), p.294-314

Ghysels, Eric

2016

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Exponential smoothing: The state of the art—Part II

International journal of forecasting, 2006-10, Vol.22 (4), p.637-666

Gardner, Everette S.

2006

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iETS: State space model for intermittent demand forecasting

International journal of production economics, 2023-11, Vol.265, p.109013, Article 109013

2023

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A quasi-Bayesian local likelihood approach to time varying parameter VAR models

Journal of econometrics, 2019-09, Vol.212 (1), p.286-306

Petrova, Katerina

2019

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Precision-based sampling for state space models that have no measurement error

Journal of economic dynamics & control, 2023-09, Vol.154, p.104720, Article 104720

Mertens, Elmar

2023

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Fast and accurate variational inference for models with many latent variables

Journal of econometrics, 2022-10, Vol.230 (2), p.339-362

2022

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Large time-varying parameter VARs

Journal of econometrics, 2013-12, Vol.177 (2), p.185-198

2013

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Models for optimising the theta method and their relationship to state space models

International journal of forecasting, 2016-10, Vol.32 (4), p.1151-1161

2016

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High-dimensional conditionally Gaussian state space models with missing data

Journal of econometrics, 2023-09, Vol.236 (1), p.105468, Article 105468

2023

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Bias compensation-based parameter and state estimation for a class of time-delay non-linear state-space models

IET control theory & applications, 2020-10, Vol.14 (15), p.2176-2185

2020

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Resolving the ambiguity of random‐effects models with singular precision matrix

Statistica Neerlandica, 2021-11, Vol.75 (4), p.482-499

2021

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The energy landscape predicts flight height and wind turbine collision hazard in three species of large soaring raptor

The Journal of applied ecology, 2017-12, Vol.54 (6), p.1895-1906

2017

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Robust Two-Step Wavelet-Based Inference for Time Series Models

Journal of the American Statistical Association, 2022-10, Vol.117 (540), p.1996-2013

2022

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Parsimony inducing priors for large scale state–space models

Journal of econometrics, 2022-09, Vol.230 (1), p.39-61

2022

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Latent local-to-unity models

Econometric reviews, 2023-08, Vol.42 (7), p.586-611

2023

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Bootstrap inference and diagnostics in state space models: With applications to dynamic macro models

Journal of applied econometrics (Chichester, England), 2022-01, Vol.37 (1), p.3-22

2022

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Large stochastic volatility in mean VARs

Journal of econometrics, 2023-09, Vol.236 (1), p.105469, Article 105469

2023

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Optimal hierarchical EWMA forecasting

International journal of forecasting, 2024-04, Vol.40 (2), p.616-625

2024

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Improving estimation of flight altitude in wildlife telemetry studies

The Journal of applied ecology, 2018-07, Vol.55 (4), p.2064-2070

2018

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Integrated variance of irregularly spaced high-frequency data: A state space approach based on pre-averaging

Studies in nonlinear dynamics and econometrics, 2023-12, Vol.27 (5), p.733-763

2023

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Bayesian Forecasting of Many Count-Valued Time Series

Journal of business & economic statistics, 2020-10, Vol.38 (4), p.872-887

2020

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On the Relationship between Uhlig Extended and beta‐Bartlett Processes

Journal of time series analysis, 2022-01, Vol.43 (1), p.147-153

2022

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Noise covariance matrices in state‐space models: A survey and comparison of estimation methods—Part I

Latent Gaussian Count Time Series

An Invitation to Sequential Monte Carlo Samplers

Macroeconomics and the reality of mixed frequency data

Exponential smoothing: The state of the art—Part II

iETS: State space model for intermittent demand forecasting

A quasi-Bayesian local likelihood approach to time varying parameter VAR models

Precision-based sampling for state space models that have no measurement error

Fast and accurate variational inference for models with many latent variables

Large time-varying parameter VARs

Models for optimising the theta method and their relationship to state space models

High-dimensional conditionally Gaussian state space models with missing data

Bias compensation-based parameter and state estimation for a class of time-delay non-linear state-space models

Resolving the ambiguity of random‐effects models with singular precision matrix

The energy landscape predicts flight height and wind turbine collision hazard in three species of large soaring raptor

Robust Two-Step Wavelet-Based Inference for Time Series Models

Parsimony inducing priors for large scale state–space models

Latent local-to-unity models

Bootstrap inference and diagnostics in state space models: With applications to dynamic macro models

Large stochastic volatility in mean VARs

Optimal hierarchical EWMA forecasting

Improving estimation of flight altitude in wildlife telemetry studies

Integrated variance of irregularly spaced high-frequency data: A state space approach based on pre-averaging

Bayesian Forecasting of Many Count-Valued Time Series

On the Relationship between Uhlig Extended and beta‐Bartlett Processes

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