Results 41 to 50 of about 5,704 (194)

Bayesian semiparametric regression models to characterize molecular evolution

BMC Bioinformatics, 2012
Background Statistical models and methods that associate changes in the physicochemical properties of amino acids with natural selection at the molecular level typically do not take into account the correlations between such properties.
Datta Saheli, Rodriguez Abel, Prado Raquel   +2 more
doaj   +1 more source

Assessing Impact of Temperature Variability of Climate Change on Mortality Based on Multiple GCM Projections in China

Atmosphere, 2022
Gradually increasing durations of high temperature caused by climate change harm the health of individuals and then lead to death. This study aimed to investigate the relationship between durations of different daily mean air-temperature categories and ...
Xiangyi Zheng, Qingyuan Ma, Ying Wang, Xia Wang, Xinren Zhang, Qingzu Luan   +5 more
doaj   +1 more source

Improving the Finite Sample Estimation of Average Treatment Effects Using Double/Debiased Machine Learning With Propensity Score Calibration

Journal of Applied Econometrics, EarlyView.
ABSTRACT Double/debiased machine learning (DML) uses for estimating an average treatment effect (ATE) a double‐robust score function that relies on the prediction of nuisance functions, such as the propensity score, which is the probability of treatment assignment given covariates.
Daniele Ballinari, Nora Bearth
wiley   +1 more source

Mapping Causal Biology: Mendelian Randomization in the Era of Big Data

Med Research, EarlyView.
Mendelian randomization (MR) leverages genetic variants to mitigate confounding biases in causal inference. This review systematically maps MR's methodological evolution, highlights its expanding applications in epidemiology and drug target validation, and outlines future directions for overcoming current biases through dynamic, multi‐omics, and cross ...
Xuanlu Shen, Chunrun Qu, Zeyu Wang, Jinglin Zhou, Hongwei Liu, Yingjie Li, Bowei Liu, Hao Zhang, Nan Zhang, Jingwei Zhang, Quan Cheng   +10 more
wiley   +1 more source

Local Eviction Moratoria and the Spread of COVID‐19

Southern Economic Journal, EarlyView.
ABSTRACT At different stages during the initial onset of the COVID‐19 pandemic, various US states and local municipalities enacted eviction moratoria. One of the main aims of these moratoria was to slow the spread of COVID‐19 infections. We deploy a semiparametric difference‐in‐differences approach with an event study specification to examine whether ...
Julia Hatamyar, Christopher F. Parmeter
wiley   +1 more source

Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification

Econometrics, 2015
Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β (
Ying-Ying Lee
doaj   +1 more source

Regulation, Taxation, and Resources: Unpacking Greenhouse Gas Emission Drivers Across G7 Economies

Thunderbird International Business Review, EarlyView.
ABSTRACT Advanced economies are under growing pressure to downscale greenhouse gas (GHG) emissions without undermining growth, yet G7 (Group of Seven) nations, representing almost 10% of the world's population, still generate one quarter of global GHGs.
Mohammad Imtiaz Hossain, Md Emon Ahmed, Mohammad Fakhrul Islam, Md. Karimul Alam, Mohammad Abdullah Al Mamun, Md Tarique Kazi   +5 more
wiley   +1 more source

Semiparametric Regression in Size‐Biased Sampling [PDF]

Biometrics, 2010
SummarySize‐biased sampling arises when a positive‐valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size‐biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of ...
openaire   +3 more sources

On semiparametric -estimation in single-index regression [PDF]

Journal of Statistical Planning and Inference, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Delecroix, Michel, Hristache, M., Patilea, Valentin   +2 more
openaire   +5 more sources

Mitigating policy uncertainty: What financial markets reveal about firm‐level lobbying

American Journal of Political Science, EarlyView.
Abstract Elections can lead to substantial policy changes and, thus, are a significant source of risk. Firms can respond to such policy uncertainty by lobbying, but it is hard to quantify whether they do so and, if so, how much lobbying benefits them. We construct a new dataset and leverage investors’ expectations of variability in stock returns in the
Kristy Buzard, Nathan Canen, Sebastian Saiegh   +2 more
wiley   +1 more source