Measuring Inequalities in Gene Co-expression Networks of HIV-1 Infection Using the Lorenz Curve and Gini Coefficient
نویسندگان
چکیده
منابع مشابه
A Rethink on Measuring Health Inequalities Using the Gini Coefficient
Objective: We show that a standardized Gini coefficient that takes into account the feasible range of health inequality for a given health attribute is a better instrument than the normal Gini coefficient for quantifying inter-individual health inequality. Methods: The standardized Gini coefficient is equal to the normal Gini coefficient divided by the maximal attainable Gini coefficient, which...
متن کاملEstimation of the Gini coefficient for the lognormal distribution of income using the Lorenz curve
The main objective of the study is to compare the Newton-Cotes methods such as the Trapezium rule, Simpson 1/3 rule and Simpson 3/8 rule to estimate the area under the Lorenz curve and Gini coefficient of income using polynomial function with degree 5. Comparing the Gini coefficients of income computed from the Polynomial function with degree 5 for the Trapezium, Simpson 1/3 and Simpson 3/8 met...
متن کاملdistribution of physicians and hospital beds based on gini coefficient and lorenz curve: a national survey
introduction: inequality is prevalent in all sectors, particularly in distribution of and access to resources in the health sector. the aim of current study was to investigate the distribution of physicians and hospital beds in iran in 2001, 2006 and 2011. methods: this retrospective, cross-sectional study evaluated the distribution of physicians and hospital beds in 2001, 2006 and 2011 using g...
متن کاملErratum to: Estimation of the Gini coefficient for the lognormal distribution of income using the Lorenz curve
[This corrects the article DOI: 10.1186/s40064-016-2868-z.].
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Data Mining in Genomics & Proteomics
سال: 2014
ISSN: 2153-0602
DOI: 10.4172/2153-0602.1000148