Results 161 to 170 of about 107,979 (335)

Shaping the System Through Turbulence: Strategic Leadership and the Micro‐Foundations of Ecosystem Orchestration in Times of Disruption

Journal of Management Studies, EarlyView.
Abstract While research on ecosystems and their orchestration has grown rapidly, we still know little about how individual strategic leaders may mobilize ecosystemic action in times of disruption. This article addresses this gap by drawing on an in‐depth case study of the Antwerp Square Mile, the world’s oldest and most renowned diamond trading ...
Bart De Keyser, Koen Vandenbempt
wiley   +1 more source

Improved deformation reconstruction of composite material structures based on optical fiber sensing. [PDF]

Sci Rep
Huang J, Sun Y, Peng Y, Zhang D, Li R, Yin S, Peng Z, Huang Q, Liu Q.   +8 more
europepmc   +1 more source

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source

Variational adaptive Gaussian approximation filter for nonlinear systems with generalized unknown disturbances. [PDF]

iScience
Qin Y, Lv J, Li S, Hou Y.
europepmc   +1 more source

Time‐Varying Dispersion Integer‐Valued GARCH Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT We introduce a general class of INteger‐valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing simultaneously time‐varying mean and dispersion parameters. We call such models time‐varying dispersion INGARCH (tv‐DINGARCH) models.
Wagner Barreto‐Souza, Luiza S. C. Piancastelli, Konstantinos Fokianos, Hernando Ombao   +3 more
wiley   +1 more source

Machine learning of factors for improving oyster hatchery production. [PDF]

PLoS One
Vishwakarma S, Gray MW, Silsbe GM, Lyubchich V.   +3 more
europepmc   +1 more source

Extremely Fast Maximum Likelihood Estimation of High‐Order Autoregressive Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT We consider the problem of exact maximum likelihood estimation of potentially high‐order (p>50$$ p>50 $$) autoregressive models. We propose an extremely fast coordinate‐wise algorithm for fitting autoregressive models. This fast algorithm exploits several properties of the negative log‐likelihood when parameterised in terms of partial ...
Daniel F. Schmidt, Enes Makalic
wiley   +1 more source

Transcriptomic analysis and machine learning have identified shared diagnostic genes and a possible mechanism linking bipolar disorder and epilepsy. [PDF]

Medicine (Baltimore)
Zhang Y, Xu Y, Huo C.
europepmc   +1 more source

Algorithms for recursive/semi-recursive bias-compensating least squares system identification within the errors-in-variables framework

, 2012
Jens G. Linden, Tomasz Larkowski, Keith J. Burnham   +2 more
openalex   +2 more sources

Online Detection of Forecast Model Inadequacies Using Forecast Errors

Journal of Time Series Analysis, EarlyView.
ABSTRACT In many organizations, accurate forecasts are essential for making informed decisions in a variety of applications, from inventory management to staffing optimization. Whatever forecasting model is used, changes in the underlying process can lead to inaccurate forecasts, which will be damaging to decision‐making.
Thomas Grundy, Rebecca Killick, Ivan Svetunkov   +2 more
wiley   +1 more source