Results 141 to 150 of about 1,472,346 (301)
State space modelling of extreme values with particle filters [PDF]
, 2009 State space models are a flexible class of Bayesian model that can be used to smoothly capture non-stationarity. Observations are assumed independent given a latent state process so that their distribution can change gradually over time. Sequential Monte
Wyncoll, David P.
core
Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state-space models. [PDF]
Stat Comput, 2021 Goldman JV, Singh SS.
europepmc +1 more source
FEBS Open Bio, EarlyView.RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
State Space Modeling Using SAS
This article provides a brief introduction to the state space modeling capabilities in SAS, a well-known statistical software system. SAS provides state space modeling in a few different settings.
Rajesh Selukar
core
Estimating Distributions of Parameters in Nonlinear State Space Models with Replica Exchange Particle Marginal Metropolis-Hastings Method. [PDF]
Entropy (Basel), 2022 Inoue H, Hukushima K, Omori T.
europepmc +1 more source
FEBS Open Bio, EarlyView.Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley +1 more source
Some Nonlinear Exponential Smoothing Models are Unstable [PDF]
This paper discusses the instability of eleven nonlinear state space models that underly exponential smoothing. Hyndman et al. (2002) proposed a framework of 24 state space models for exponential smoothing, including the well-known simple exponential ...
Rob J Hyndman, Muhammad Akram
core
FEBS Open Bio, EarlyView.Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
Efficient Likelihood Evaluation of State-Space Representations [PDF]
We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models.
David N. DeJong +4 more
core
Using Bayesian state-space models to understand the population dynamics of the dominant malaria vector, Anopheles funestus in rural Tanzania. [PDF]
Malar J, 2022 Ngowo HS +5 more
europepmc +1 more source