Results 131 to 140 of about 1,472,346 (301)

Forecasting VARMA processes using VAR models and subspace-based state space models

VAR modelling is a frequent technique in econometrics for linear processes. VAR modelling offers some desirable features such as relatively simple procedures for model specification (order selection) and the possibility of obtaining quick non-iterative ...
del Hoyo, Juan, Hernández, Cesáreo, Izquierdo, Segismundo S.   +2 more
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Block Sampler and Posterior Mode Estimation for A Nonlinear and Non-Gaussian State-Space Model with Correlated Errors [PDF]

This article introduces a new efficient simulation smoother and disturbance smoother for general state-space models where there exists a correlation between error terms of the measurement and state equations.
Toshiaki Watanabe, Yasuhiro Omori
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Identification of nonlinear lateral flow immunoassay state-space models via particle filter approach

, 2012
This is the post-print of the Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, the particle filtering approach is used, together with the kernel smoothing method, to identify the state ...
Zidong Wang, Min Du, Zeng, N, Liu, X, Wang, Z, Nianyin Zeng, Xiaohui Liu, Li, Y, Yurong Li, Du, M   +9 more
core   +1 more source

On Epistemics in Expected Free Energy for Linear Gaussian State Space Models. [PDF]

Entropy (Basel), 2021
Koudahl MT, Kouw WM, de Vries B.
europepmc   +1 more source

From tumor‐centric to ecosystem‐based hypotheses in brain tumor research and care

Molecular Oncology, EarlyView.
Primary brain tumors, whether in adults or children, present a major challenge because of their dramatic prognosis and the ongoing lack of efficient therapeutic approaches. In recent years, a shift has occurred from tumor‐centric concepts to a more holistic view of these tumors as dynamic ecosystems.
Julie Gavard, Flavie Bénard, Eva Billat, Margaux Le Guyon, Victoria Maltret, Laura Merlet, Chloé Astrid Walter, Tony Avril, Eric Chevet   +8 more
wiley   +1 more source

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form [PDF]

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model.
Neil Shephard, Charles S. Bos
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Modelling menstrual cycle length in athletes using state-space models. [PDF]

Sci Rep, 2021
de Paula Oliveira T, Bruinvels G, Pedlar CR, Moore B, Newell J.   +4 more
europepmc   +1 more source

Preoperative circulating tumor cells integrated with imaging analysis for prognostic evaluation in head and neck squamous cell carcinoma

Molecular Oncology, EarlyView.
Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach, Gizem Abaci, Tom Huberty, Axel Lechner, Lukas Käsmann, Jens Ricke, Sophia Stöcklein, Martin Canis, Philipp Baumeister, Marianna Alunni‐Fabbroni   +9 more
wiley   +1 more source

State Space Modeling Using SsfPack in S+FinMetrics 3.0

This paper presents two illustrations of state space modeling in S-PLUS using the SsfPack 3.0 routines implemented in S+FinMetrics 3.0. The state space modeling functions in S+FinMetrics/SsfPack are extremely flexible and powerful and can be used for a ...
Eric W. Zivot
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Improvement of surface water quality variables modelling that incorporates a hydro-meteorological factor: a state-space approach

, 2011
In this work it is constructed a hydro-meteorological factor to improve the adjustment of statistical time series models, such as state space models, of water quality variables by observing hydrological series (recorded in time and space) in a River ...
Gonçalves, A. Manuela, Costa, Marco
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