21 papers · ranked by Valyu relevance
Vita Ratnasari, Salsabila Hidayatul Audha, Andrea Tri Rian Dani
Title: Review Highlights 1. • Regression modeling with panel data. 2. • The observation units used are provinces in Indonesia based on inter-regional disaggregation variables in modeling the middle-income trap problem.
Lingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi
This paper introduces the problem of coresets for regression problems to panel data settings. We first define coresets for several variants of regression problems with panel data and then present efficient algorithms to construct coresets of size that depend polynomially on 1/ε (where ε is the error parameter) and the…
Jiwoong Kim
This paper studies the minimum distance estimation problem for panel data model. We propose the minimum distance estimators of regression parameters of the panel data model and investigate their asymptotic distributions. This paper contains two main contributions. First, the domain of application of the minimum…
Rabnawaz Khan
Agriculture is the dominant economic activity of the economies. The developing and developed countries are responsible for the most greenhouse gasses emitted in the developing areas. Are there heterogeneous determinants of environmental degradation and CO2 emitters in developing and developed countries? and estimating…
Debbie J. Dupuis, Sebastian Engelke, Luca Trapin
> Extreme value applications commonly employ regression techniques to capture cross-sectional heterogeneity or time-variation in the data. Estimation of the parameters of an extreme value regression model is notoriously challenging due to the small number of observations that are usually available in applications. When…
Ming Guan
Background Currently, the knowledge of associations among newly recovered cases (NR), newly healed cases (NH), newly confirmed cases (NC), and newly dead cases (ND) can help to monitor, evaluate, predict, control, and curb the spreading of coronavirus disease 2019 (COVID-19). This study aimed to explore the panel…
Li Tao, Lingnan Tai, Maozai Tian, Mahdi Roozbeh
This paper proposes two new weighted quantile regression estimators for static panel data model with time-invariant regressors. The two new estimators can improve the estimation of the coefficients with time-invariant regressors, which are computationally convenient and simple to implement. Also, the paper shows…
Sinem Koçak, Özge Barış-Tüzemen
The study explores the role of the COVID-19 pandemic on foreign direct investment in 12 emerging countries for the period between 2014 and 2021. The world pandemic uncertainty index is used, and panel quantile regression approach is employed to analyze the effect of the pandemic on foreign investment inflows. Unlike…
Beste Hamiye Beyaztaş, Soutir Bandyopadhyay
The panel data regression models have gained increasing attention in different areas of research including but not limited to econometrics, environmental sciences, epidemiology, behavioral and social sciences. However, the presence of outlying observations in panel data may often lead to biased and inefficient…
Beste Hamiye Beyaztaş, Soutir Bandyopadhyay
In different fields of applications including, but not limited to, behavioral, environmental, medical sciences and econometrics, the use of panel data regression models has become increasingly popular as a general framework for making meaningful statistical inferences. However, when the ordinary least squares (OLS)…
Abhijit Mandal, Beste Hamiye Beyaztaş, Soutir Bandyopadhyay
The panel data regression models have become one of the most widely applied statistical approaches in different fields of research, including social, behavioral, environmental sciences, and econometrics. However, traditional least-squares-based techniques frequently used for panel data models are vulnerable to the…
YuSheng Kong, Rabnawaz Khan
This study analyzes the core energy consumption among countries specific variables by Environmental Kuznets Curve hypothesis (EKC), for a panel data of 29 (14 developed and 15 developing) countries during the period of 1977-2014. By assessing Generalized Method of Moments (GMM) regressions with first generation test…
Julian D. Karch, Andreas M. Brandmaier, Manuel C. Voelkle
In this article, we extend the Bayesian nonparametric regression method Gaussian Process Regression to the analysis of longitudinal panel data. We call this new approach Gaussian Process Panel Modeling (GPPM). GPPM provides great flexibility because of the large number of models it can represent. It allows classical…
Jordan Anaya, John-William Sidhom, Craig A. Cummings, Alexander S. Baras
Tumor mutational burden (TMB) has been investigated as a biomarker for immune checkpoint blockade (ICB) therapy. Increasingly, TMB is being estimated with gene panel-based assays (as opposed to full exome sequencing) and different gene panels cover overlapping but distinct genomic coordinates, making comparisons across…
Mikihito Nishi, Ryo Okui
This paper introduces statistical inference procedures for unit-specific coefficients in panel data models, where the coefficients exhibit a latent group structure. The proposed methods achieve efficiency gains by clustering units into a small number of groups, while explicitly accounting for the statistical…
Yijun Wang, Weiwei Wang, Feng Chen
Panel count data frequently occurs in follow-up studies, such as medical research, social sciences, reliability studies, and tumorigenicity experiences. This type data has been extensively studied by various statistical models with time-invariant regression coefficients. However, the assumption of invariant…
Sebastian Kocar, Nicholas Biddle
The objective of this study is to identify factors affecting participation rates, i.e., nonresponse and voluntary attrition rates, and their predictive power in a probability-based online panel. Participation for this panel had already been investigated in the literature according to the socio-demographic and…
Satoshi Usami, Naoya Todo, Kou Murayama
Longitudinal designs provide a strong inferential basis for uncovering reciprocal effects or causality between variables. For this analytic purpose, a cross-lagged panel model (CLPM) has been widely used in medical research, but the use of the CLPM has recently been criticized in methodological literature because…
Jordan Anaya, John-William Sidhom, Craig A. Cummings, Alexander S. Baras
Deep learning has the ability to extract meaningful features from data given enough training examples. Large scale genomic data are well suited for this class of machine learning algorithms; however, for many of these data the labels are at the level of the sample instead of at the level of the individual genomic…
Kan Hatakeyama-Sato, Seigo Watanabe, Naoki Yamane, Yasuhiko Igarashi + 1 more
Materials informatics and cheminformatics struggle with data scarcity, hindering the extraction of significant relationships between structures and properties. The "Ugly Duckling" theorem, suggesting the difficulty of data processing without assumptions or prior knowledge, exacerbates this problem. Current…
Authors not listed
Bonkowski and De Souza [Sol. Stat. Ionics 429, 116967 (2025)] provide a guide for performing molecular dynamics simulations of ion transport, including methods for estimating diffusion coefficients and their uncertainties from mean-squared displacement (MSD) data. The discussion of uncertainty in estimated diffusion…