Bayesian inference in based-kernel regression: comparison of count data of condition factor of fish in pond systems [0.03%]
基于核的回归中的贝叶斯推断：比较池塘系统中鱼类状况数据
T Senga Kiessé,Etienne Rivot,Christophe Jaeger et al.
T Senga Kiessé et al.
The discrete kernel-based regression approach generally provides pointwise estimates of count data that do not account for uncertainty about both parameters and resulting estimates. This work aims to provide probabilistic kernel estimates o...
On a generalization of the test of endogeneity in a two stage least squares estimation [0.03%]
两阶段最小二乘估计中内生性检验的推广研究
Ayyub Sheikhi,Fatemeh Bahador,Mohammad Arashi
Ayyub Sheikhi
In situations that the predictors are correlated with the error term, we propose a bridge estimator in the two-stage least squares estimation. We apply this estimator to overcome the multicollinearity and sparsity of the explanatory variabl...
Maria Anastasopoulou,Athanasios C Rakitzis
Maria Anastasopoulou
In this work, we develop and study upper and lower one-sided EWMA control charts for monitoring correlated counts with finite range. Often in practice, data of that kind can be adequately described by a first-order binomial or beta-binomial...
A Bayesian shared parameter model for joint modeling of longitudinal continuous and binary outcomes [0.03%]
一种贝叶斯共享参数模型用于连续和二元纵向数据的联合建模
T Baghfalaki,M Ganjali,A Kabir et al.
T Baghfalaki et al.
Joint modeling of associated mixed biomarkers in longitudinal studies leads to a better clinical decision by improving the efficiency of parameter estimates. In many clinical studies, the observed time for two biomarkers may not be equivale...
A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles in oncology [0.03%]
一种用于在高度依赖性数据中选择协变量的统计方法。在肿瘤学遗传谱型分类中的应用
B Bastien,T Boukhobza,H Dumond et al.
B Bastien et al.
We propose a new methodology for selecting and ranking covariates associated with a variable of interest in a context of high-dimensional data under dependence but few observations. The methodology successively intertwines the clustering of...
The GLM framework of the Lee-Carter model: a multi-country study [0.03%]
基于Lee-Carter模型的广义线性模型框架：多国分析研究
Shafiqah Azman,Dharini Pathmanathan
Shafiqah Azman
The Lee-Carter model is a well-known model in modeling mortality. We aim to compare three probability models (Poisson, negative binomial and binomial) based on the Generalized Linear Model (GLM) framework of the Lee-Carter model. These mode...
Qingguo Tang,Rohana J Karunamuni,Boxiao Liu
Qingguo Tang
In this paper, we investigate robust parameter estimation and variable selection for binary regression models with grouped data. We investigate estimation procedures based on the minimum-distance approach. In particular, we employ minimum H...
A Baíllo,J E Chacón
A Baíllo
The home range of an animal describes the geographic area where this individual spends most of the time while doing its usual activities. From a statistical viewpoint, the problem of home range estimation can be considered as a set estimati...
A proportional-hazards model for survival analysis and long-term survivors modeling: application to amyotrophic lateral sclerosis data [0.03%]
生存分析及长期存活者模型的propotional-hazards模型——应用ALS数据进行演示
Tasnime Hamdeni,Soufiane Gasmi
Tasnime Hamdeni
The majority of survival data are affected by explanatory variables. We develop a new regression model for survival data analysis. As an alternative to standard mixture models, another model is proposed to describe the eventual presence of ...
A semi-analytical solution to the maximum-likelihood fit of Poisson data to a linear model using the Cash statistic [0.03%]
卡什统计量的泊松数据拟合直线模型的最大似然解的半解析解法
Massimiliano Bonamente,David Spence
Massimiliano Bonamente
The Cash statistic, also known as the C statistic, is commonly used for the analysis of low-count Poisson data, including data with null counts for certain values of the independent variable. The use of this statistic is especially attract...