B L Robertson,C J Price,M Reale et al.
B L Robertson et al.
Generalised Random Tessellation Stratified (GRTS) is a popular spatially balanced sampling design. GRTS can draw spatially balanced probability samples in two dimensions but has not been used to sample higher-dimensional auxiliary spaces. T...
Lasso Monte Carlo, a variation on multi fidelity methods for high-dimensional uncertainty quantification [0.03%]
一种用于高维度不确定性量化的方法-lasso蒙特卡洛方法及其多 fidelity变体方法的研究
Arnau Albà,Romana Boiger,Dimitri Rochman et al.
Arnau Albà et al.
Uncertainty quantification (UQ) is an active area of research, and an essential technique used in all fields of science and engineering. The most common methods for UQ are Monte Carlo and surrogate-modelling. The former method is dimensiona...
An R tool for computing and evaluating Fuzzy poverty indices: The package FuzzyPovertyR [0.03%]
一个用于计算和评估模糊贫困指数的R工具：FuzzyPovertyR包
F Crescenzi,L Mori,G Betti et al.
F Crescenzi et al.
Fuzzy set theory has become increasingly popular for deriving uni- and multi-dimensional poverty estimates. In recent years, various authors have proposed different approaches to defining membership functions, resulting in the development o...
Forecasting a time series of Lorenz curves: one-way functional analysis of variance [0.03%]
洛伦兹曲线时间序列的预测：单向函数方差分析
Han Lin Shang
Han Lin Shang
The Lorenz curve is a fundamental tool for analysing income and wealth distribution and inequality at national and regional levels. We utilise a one-way functional analysis of variance to decompose a time series of Lorenz curves and develop...
Estimation of quantile versions of the Lorenz curve and the Gini index for the generalized Pareto distribution [0.03%]
广义Pareto分布的洛伦兹曲线和基尼指数的分位数估计方法
Alicja Jokiel-Rokita,Agnieszka Siedlaczek
Alicja Jokiel-Rokita
This paper concerns the estimation of quantile versions of the Lorenz curve and the Gini index in the case of the generalized Pareto distribution. These curves and indices, unlike the Lorenz curve and the Gini index, are also defined for di...
LPRE estimation for functional multiplicative model and optimal subsampling [0.03%]
函数型加性模型的LPRE估计及其最优亚抽样方法
Qian Yan,Hanyu Li
Qian Yan
In this paper, we study the functional linear multiplicative model based on the least product relative error criterion. Under some regularization conditions, we establish the consistency and asymptotic normality of the estimator. Further, w...
Identifying outlying groups through residual analysis and its application to healthcare expenditure [0.03%]
基于残差分析的异常组检测及其在卫生费用分析中的应用
Hyukdong Kwon,Jihnhee Yu,Mingliang Li
Hyukdong Kwon
Traditional regression analysis primarily aims to describe the overall relationship between variables, often overlooking unexplainable aspects by design. Our focus is on these unexplained aspects, leveraging them to identify disparity group...
Multivariate meta-analysis with a robustified diagonal likelihood function [0.03%]
一种鲁棒的对角似然函数在线性混合模型中的应用
Zongliang Hu,Qianyu Zhou,Guanfu Liu
Zongliang Hu
Multivariate meta-analysis is an efficient tool to analyze multivariate outcomes from independent studies, with the advantage of accounting for correlations between these outcomes. However, existing methods are sensitive to outliers in the ...
New strategies for detecting atypical observations based on the information matrix equality [0.03%]
基于信息矩阵相等性的检测异常观测的新策略
Francisco Cribari-Neto,Klaus L P Vasconcellos,José J Santana-E-Silva
Francisco Cribari-Neto
Diagnostic analyses in regression modeling are usually based on residuals or local influence measures and are used for detecting atypical observations. We develop a new approach for identifying such observations when the parameters of the m...
Order selection in GARMA models for count time series: a Bayesian perspective [0.03%]
计数时间序列的GARMA模型订单选择：贝叶斯视角
Katerine Zuniga Lastra,Guilherme Pumi,Taiane Schaedler Prass
Katerine Zuniga Lastra
Estimation in GARMA models has traditionally been carried out under the frequentist approach. To date, Bayesian approaches for such estimation have been relatively limited. In the context of GARMA models for count time series, Bayesian esti...