Application of seasonal-adjusted hybrid models for forecasting Discomfort Index in a heat-prone region of Bangladesh. [PDF]
Binte Ahmed A +5 more
europepmc +1 more source
A Comprehensive Revisit to the Safe‐Haven Assets Literature
ABSTRACT A large number of studies examine the safe‐haven characteristics of different asset classes. However, this paper addresses a lack of systematic literature reviews and bibliometric analyses with a sound theoretical viewpoint the safe‐haven assets literature by focusing on 1305 studies published in top‐tier journals during 2013–2026 from the ...
Javed Bin Kamal +3 more
wiley +1 more source
National and regional Temporal trends and forecasting of preterm birth in brazil: evidence from National birth data (2014-2023) with projections to 2030. [PDF]
Victor A +8 more
europepmc +1 more source
ABSTRACT Despite their transformative potential, Industrial Internet of Things (IIoT) platforms often fail to evolve into scalable ecosystems. Research on IIoT platforms attributes failure to discrete factors such as governance misalignment or technological complexity and rarely considers how failure unfolds.
Philipp Kernstock +3 more
wiley +1 more source
Summary The interplay of daily life factors, including mood, physical activity, or light exposure, influences sleep architecture and quality. Laboratory‐based studies often isolate these determinants to establish causality, thereby sacrificing ecological validity.
Anna M. Biller +8 more
wiley +1 more source
Dynamic forecasting and mechanisms of volatility synchronization in complex financial systems. [PDF]
Li JC, Guo J, Ma R, Zhong G.
europepmc +1 more source
Change Point Analysis for Functional Data Using Empirical Characteristic Functionals
ABSTRACT We develop a new method to detect change points in the distribution of functional data based on integrated CUSUM processes of empirical characteristic functionals. Asymptotic results are presented under conditions allowing for low‐order moments and serial dependence in the data establishing the limiting null‐distribution of the proposed test ...
Lajos Horváth +2 more
wiley +1 more source
Value at Risk long memory volatility models with heavy-tailed distributions for cryptocurrencies. [PDF]
Subramoney SD, Chinhamu K, Chifurira R.
europepmc +1 more source
Time‐Varying Dispersion Integer‐Valued GARCH Models
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 +3 more
wiley +1 more source
Hybrid time series and machine learning models for forecasting cardiovascular mortality in India: an age specific analysis. [PDF]
Teja MD, Rayalu GM.
europepmc +1 more source

