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Asymptotic Analysis of Regression Quantile Estimators for Real-Valued Chirp Signal Model
In this paper, we consider the problem of robust estimation of parameters of a 1-dimensional chirp signal model. We propose regression quantile...
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The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications
In this paper, we propose and derive a new regression model for response variables defined on the open unit interval. By reparameterizing the unit...
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Bitcoin Price Forecasting Through Crypto Market Variables: Quantile Regression and Machine Learning Approaches
The cryptocurrency market is an innovative alternative to the traditional currency markets that has increased the interest of investors, academics,...
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Effects of Household Income and Parental Absence on Investment in Child Education in Thailand: Evidence from Quantile-on-Quantile Approach
This study estimates the income elasticity of educational expenditure for Thai households, that is, how much Thai households would increase their...
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Comparison of Entropy Measures in Panel Quantile Regression and Applications to Economic Growth Analysis
The three entropy measures (Shannon, Tsallis, and Renyi entropy) are used as the objective of the entropy functions in Generalized Maximum...
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Monte Carlo Method and Quantile Regression for Uncertainty Analysis of Wind Power Forecasting Based on Chaos-LS-SVM
In the paper, the chaos least squares support vector machine algorithm (Chaos-LS-SVM) is applied. To conduct uncertainty analysis of wind power...
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High Frequency-Based Quantile Forecast and Combination: An Application to Oil Market
This paper investigates how the high frequency-based models and forecast combination can improve the accuracy of quantile forecasts. Using...
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Copula-Based Stochastic Frontier Quantile Model with Unknown Quantile
This study aims to improve the copula-based stochastic frontier quantile model by treating the quantile as the unknown parameter. This method can...
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An Invitation to Multivariate Quantiles Arising from Optimal Transport Theory
While a variety of new concepts and methods arised from Optimal Transport theory recently in the literature, they are somewhat theoretical for...
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An adaptive trimming approach to Bayesian additive regression trees
A machine learning technique merging Bayesian method called Bayesian Additive Regression Trees (BART) provides a nonparametric Bayesian approach that...
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Statistical Inferences for Multivariate Generalized Gamma Regression Model
Generalized gamma (GG) distribution serves as a widely applied statistical tool, particularly suitable for scenarios where data distribution skews...
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A Systematic Survey on Implementation of Fuzzy Regression Models for Real Life Applications
Regression analysis is a statistical method employed to establish the relationship between "independent variables" and "dependent variables." This...
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Decoding COVID-19 Vaccine Hesitancy Using Multiple Regression Analysis with Socioeconomic Values
With the growth and development of COVID-19 and its variants, reaching a level of herd immunity is critically important for national security in...
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Socioeconomic Inequality Exacerbated by COVID-19: A Multiple Regression Analysis with Income, Healthcare Insurance, and Mask Use
The increase in income and health insurance coverage inequality contributes to an increase in COVID-19 incidences. Wearing masks can reduce the...
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Taming the Complexity of Distributed Lag Models: A Practical Approach to Multicollinearity, Outliers, and Auto-Correlation in Finance
This research investigates the application of robust estimators within the finite distributed lag model (DLM), a critical framework in finance...
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The Interplay Between Interest Rates, Volatility, and Herding: Insights from the Chinese Shanghai Stock Market
This study examines the intricate relationship between interest rates, herding behaviour, and volatility’s mediating role within the Chinese Shanghai...
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A working likelihood approach to support vector regression with a data-driven insensitivity parameter
The insensitivity parameter in support vector regression determines the set of support vectors that greatly impacts the prediction. A data-driven...
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A Quantile Regression approach for the analysis of the diversification in non-life premium risk
This paper concerns the study of the diversification effect involved in a portfolio of non-life policies priced via traditional premium principles...
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The Asymmetric Effect of Trade, Financial, and Political Globalization on Economic Development in ASEAN+3
This study investigates the heterogeneous effect of trade globalization, financial globalization and political globalization on economic development...
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Robust LASSO and Its Applications in Healthcare Data
We address the development of a robust variable selection procedure using the density power divergence with the least absolute shrinkage and...