SIMEX Estimation in Parametric Modal Regression with Measurement Error

基于SIMEX估计真实效应量分布

Estimating the True Effect Size Distribution with SIMEX

针对大规模在线实验含噪声效应估计的问题，提出基于SIMEX的非参数方法，可从已知方差的估计平均处理效应中估计真实效应分布，性能接近参数经验贝叶斯方法，为表征效应量分布提供灵活途径。

参数模态回归用于右截断正响应

Parametric modal regression for right-censored positive responses

本文提出了一种参数模态回归框架，用于处理右截断正响应，通过重新参数化将模式与线性预测变量直接关联，并通过实证数据验证了方法的有效性。

通过间距与双峰软件库进行模态分析

Modality Analysis via Spacing with the Dimodal Software Libraries

研究通过间距与双峰软件库进行模态分析，介绍了包含多种测试的R包Dimodal，描述其实现与性能，应用于识别小行星带柯克伍德空隙，还展示了软件端口，如DimodalCPy命令行程序。

Generalizing the log-Moyal distribution and regression models for heavy tailed loss data

Catastrophic loss data are known to be heavy-tailed. Practitioners then need models that are able to capture both tail and modal parts of claim data. To this purpose, a new parametric family of loss distributions is proposed as a gamma mixture of the generalized log-Moyal distribution from Bhati and Ravi (2018), termed the generalized log-Moyal gamma distribution (GLMGA). We discuss the probabilistic characteristics of the GLMGA, and statistical estimation of the parameters through maximum likelihood. While the GLMGA distribution is a special case of the GB2 distribution, we show that this sim…

协变量含误差的参数众数回归

Parametric Modal Regression with Error in Covariates

本文针对协变量含测量误差的众数回归模型，提出一致参数估计方法和基于参数自助法的得分诊断工具，并通过模拟与实际数据验证其有效性。

Locating γ-Ray Sources on the Celestial Sphere via Modal Clustering

Searching for as yet undetected gamma-ray sources is a major target of the Fermi LAT Collaboration. We present an algorithm capable of identifying such type of sources by non-parametrically clustering the directions of arrival of the high-energy photons detected by the telescope onboard the Fermi spacecraft. n particular, the sources will be identified using a von Mises-Fisher kernel estimate of the photon count density on the unit sphere via an adjustment of the mean-shift algorithm to account for the directional nature of data. This choice entails a number of desirable benefits. It allows us…