simplexreg: An R Package for Regression Analysis of Proportional Data Using the Simplex Distribution

被引:29
|
作者
Zhang, Peng [1 ]
Qiu, Zhenguo [2 ]
Shi, Chengchun [3 ]
机构
[1] Zhejiang Univ, Dept Math, Hangzhou 310027, Zhejiang, Peoples R China
[2] Alberta Hlth Serv, Surveillance, CancerControl, Edmonton, AB T5J 3H1, Canada
[3] North Carolina State Univ, Dept Stat, Raleigh, NC 27606 USA
来源
JOURNAL OF STATISTICAL SOFTWARE | 2016年 / 71卷 / 11期
关键词
dispersion models; proportional data; random variable generation; R; simplex distribution; GENERALIZED LINEAR-MODELS; VIABLE CD34(+) CELLS; MARGINAL MODELS; BETA REGRESSION; ENGRAFTMENT; DISPERSION; RESPONSES;
D O I
10.18637/jss.v071.i11
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Outcomes of continuous proportions arise in many applied areas. Such data are typically measured as percentages, rates or proportions confined in the unitary interval. In this paper, the R package simplexreg which provides dispersion model fitting of the simplex distribution is introduced to model such proportional outcomes. The maximum likelihood method and generalized estimating equations techniques are available for parameter estimation in cross-sectional and longitudinal studies, respectively. This paper presents methods and algorithms implemented in the package, including parameter estimation, model checking as well as density, cumulative distribution, quantile and random number generating functions of the simplex distribution. The package is applied to real data sets for illustration.
引用
收藏
页码:1 / 21
页数:21
相关论文
共 50 条
  • [31] GCA: an R package for genetic connectedness analysis using pedigree and genomic data
    Haipeng Yu
    Gota Morota
    BMC Genomics, 22
  • [32] A Distributed Regression Analysis Application Package Using SAS
    Her, Qoua L.
    Li, Dongdong
    Vilk, Yury
    Young, Jessica
    Zhang, Zilu
    Malenfant, Jessica M.
    Malek, Sarah
    Toh, Sengwee
    STATISTICS IN BIOSCIENCES, 2024,
  • [33] ordinalgmifs: An R Package for Ordinal Regression in High-dimensional Data Settings
    Archer, Kellie J.
    Hou, Jiayi
    Zhou, Qing
    Ferber, Kyle
    Layne, John G.
    Gentry, Amanda E.
    CANCER INFORMATICS, 2014, 13 : 187 - 195
  • [34] Introducing zoid: A mixture model and R package for modeling proportional data with zeros and ones in ecology
    Jensen, Alexander J.
    Kelly, Ryan P.
    Anderson, Eric C.
    Satterthwaite, William H.
    Shelton, Andrew Olaf
    Ward, Eric J.
    ECOLOGY, 2022, 103 (11)
  • [35] Sensitivity analysis for variance parameters in Bayesian simplex mixed models for proportional data
    Lopez Quintero, Freddy Omar
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2017, 46 (07) : 5212 - 5228
  • [36] Learning from Data Using the R Package "frbs"
    Septem Riza, Lala
    Bergmeir, Christoph
    Herrera, Francisco
    Manuel Benitez, Jose
    2014 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2014, : 2149 - 2155
  • [37] Simulating Survival Data Using the simsurv R Package
    Brilleman, Samuel L.
    Wolfe, Rory
    Moreno-Betancur, Margarita
    Crowther, Michael J.
    JOURNAL OF STATISTICAL SOFTWARE, 2021, 97 (03): : 1 - 27
  • [38] stab: An R package for drug stability data analysis
    Lee, Hsin-ya
    Wu, Pao- chu
    Lee, Yung-jin
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2010, 100 (02) : 140 - 148
  • [39] Rchimerism An R Package for Automated Chimerism Data Analysis
    Siddiqui, Zohair
    Maldonado, Juan
    Grojean, Jeremy
    Ye, Fei
    Zhang, David
    Longtine, Janina
    Ahn, Tae-Hyuk
    Guo, Huazhang
    JOURNAL OF MOLECULAR DIAGNOSTICS, 2020, 22 (01): : 21 - 29
  • [40] renz: An R package for the analysis of enzyme kinetic data
    Juan Carlos Aledo
    BMC Bioinformatics, 23