Results 221 to 230 of about 102,342 (297)

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

Welfare consequences of the compound risks of index insurance

Journal of Risk and Insurance, EarlyView.
Abstract Index insurance is an attractive variant on the standard insurance contract that allows the determination of a loss event to be defined by one or more thresholds on an index that is positively correlated with actual losses. Index insurance also comes with a compound risk, basis risk.
Glenn Harrison, Jimmy Martí­nez‐Correa, Karlijn Morsink, Jia Min Ng, J. Todd Swarthout   +4 more
wiley   +1 more source

Bidimensionally partitioned online sequential broad learning system for large-scale data stream modeling. [PDF]

Sci Rep
Guo W, Yu J, Zhou C, Yuan X, Wang Z.
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

Data-Driven Modeling and Predictive Control of a High-Quality Special Steel Electroslag Remelting Process with Time Delay. [PDF]

ACS Omega
Jiang X, Wang Y, Kong S, Yu H, Dong S.
europepmc   +1 more source

Tests for Changes in Count Time Series Models With Exogenous Covariates

Journal of Time Series Analysis, EarlyView.
ABSTRACT We deal with a parametric change in models for count time series with exogenous covariates specified via the conditional distribution, i.e., with integer generalized autoregressive conditional heteroscedastic models with covariates (INGARCH‐X).
Šárka Hudecová, Marie Hušková
wiley   +1 more source

Two-dimensional positioning of the crab pulsar with avoidance of non-sensitive direction. [PDF]

Sci Rep
Chen J, Zhang H, Liu J, Ma X, Ning X.
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