Results 181 to 190 of about 63,609 (288)

Analyzing the Effect of Factors on Individuals' Subjective Well-Being with Quantile Bayesian Structural Equation Modeling Approach. [PDF]

Behav Sci (Basel)
Çiçek Z, Bayram Arlı N.
europepmc   +1 more source

Distributional and Tail‐Dependent Perspectives in Economic Relationships: A Review of Quantile Regression Application

Journal of Economic Surveys, EarlyView.
ABSTRACT There is an increased proportion of studies using quantile‐based regression methodology (QR) in economics. They offer a robust alternative to classical mean regressions, which can estimate non‐normal variables with distributional heterogeneity in the dependent variable.
Shajara Ul‐Durar, Konstantinos A. Dimitriadis, Noman Arshed, Marco De Sisto, Hamidreza Harati   +4 more
wiley   +1 more source

Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach. [PDF]

Entropy (Basel)
Chen R, Chen Z.
europepmc   +1 more source

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

Journal of Economic Surveys, EarlyView.
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte, Konstantinos N. Konstantakis, Dimitris Konstantios, Panayotis G. Michaelides, Arsenios‐Georgios N. Prelorentzos   +4 more
wiley   +1 more source

Central statistical monitoring in clinical trial management: A scoping review. [PDF]

Clin Trials
Fronc M, Jakubczyk M, Love SB, Talbot S, Rolfe T.   +4 more
europepmc   +1 more source

Artificial Intelligence in Climate and Sustainable Finance: A Blessing or a Curse?

Journal of Economic Surveys, EarlyView.
ABSTRACT While there are concerns regarding the sustainability of artificial intelligence (AI), it is a potential ally in the transition toward a greener future. It offers advanced tools for data analysis; risk modeling; and environmental, social, and governance (ESG) assessment.
Filippo di Pietro, Pilar Giráldez‐Puig, Pedro R. Palos‐Sánchez, Zbigniew Korzeb   +3 more
wiley   +1 more source

Real-World Data and Causal Machine Learning to Enhance Drug Development. [PDF]

Ther Innov Regul Sci
Anagnostopoulos C, Van Der Schaar M, Collet JP, Vecino RH.   +3 more
europepmc   +1 more source

Model Ambiguity versus Model Misspecification in Dynamic Portfolio Choice

The Journal of Finance, EarlyView.
ABSTRACT We study aversion to model ambiguity and misspecification in dynamic portfolio choice. Risk‐averse investors (relative risk aversion γ>1$\gamma > 1$) fear return persistence, while risk‐tolerant investors (0<γ<1$0<\gamma <1$) fear mean reversion, when confronting model misspecification concerns of identically and independently distributed (IID)
PASCAL J. MAENHOUT, HAO XING, ANNE G. BALTER   +2 more
wiley   +1 more source

BAYESIAN DIFFERENTIAL CAUSAL DIRECTED ACYCLIC GRAPHS FOR OBSERVATIONAL ZERO-INFLATED COUNTS WITH AN APPLICATION TO TWO-SAMPLE SINGLE-CELL DATA. [PDF]

Ann Appl Stat
Choi J, Chapkin RS, Ni Y.
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