Results 71 to 80 of about 30,733 (250)
Estimation of nonparametric conditional moment models with possibly nonsmooth moments [PDF]
This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables.
Demian Pouzo, Xiaohong Chen
core +3 more sources
Environmental and Climate Technologies, 2023 This study investigates the role of environmental policies and regulations in mitigating climate change by promoting clean innovations and discouraging dirty ones.
Balcilar Mehmet, Agan Busra
doaj +1 more source
Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations
Quality and Reliability Engineering International, EarlyView.ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim +3 more
wiley +1 more source
Nonparametric Econometrics: The np Package
Journal of Statistical Software, 2008 We describe the R np package via a series of applications that may be of interest to applied econometricians. The np package implements a variety of nonparametric and semiparametric kernel-based estimators that are popular among econometricians.
Tristen Hayfield, Jeffrey S. Racine
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Bootstrap-quantile ridge estimator for linear regression with applications.
PLoS ONEBootstrap is a simple, yet powerful method of estimation based on the concept of random sampling with replacement. The ridge regression using a biasing parameter has become a viable alternative to the ordinary least square regression model for the ...
Irum Sajjad Dar, Sohail Chand
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IEEE Access, 2020 With the rapid growth of photovoltaic (PV) power in recent years, the stability of system operation, the performance of system contingency analysis as well as the power quality of the power grid are threatened by the inherent uncertainty and fluctuation ...
Fei Mei +7 more
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A note on the use of quantile regression in beta convergence analysis [PDF]
We discuss how to interpret conflicting results obtained by the use of quantile regression methods in growth regression tests of β-convergence hypothesis and the results obtained by nonparametric methods.
Marcio Laurini
core
A Robust Self‐Starting Bayesian Approach for Multivariate Phase II Monitoring
Quality and Reliability Engineering International, EarlyView.ABSTRACT Traditional multivariate control charts require in‐control (IC) parameter estimates to be known or estimated from a large set of uncontaminated, historical Phase I observations. However, some processes need to be monitored when little Phase I data are available, and self‐starting approaches, including Bayesian methods, have proven useful. Self‐
Taylor R. Grimm +2 more
wiley +1 more source
Sustainable Development, EarlyView.ABSTRACT Technological innovation and digitalization are widely viewed as key drivers of sustainable development, yet their effectiveness in reducing carbon emissions remains uncertain. This study examines how technological innovation, digitalization, energy structure, and economic activity shape both CO2 emissions and total factor productivity in 22 ...
Muhammad Waqas Khalid +2 more
wiley +1 more source
SOME PROPERTIES OF SPATIAL QUANTILES
Acta Universitatis Lodziensis. Folia Oeconomica, 2014 Conditional quantiles are required in various economic, biomedical or industrial problems. Lack of objective basis for ordering multivariate observations is a major problem in extending the notion of quantiles or conditional quantiles (also called ...
Grażyna Trzpiot
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