Yang Liu
Yang Liu
Overdispersion is a common phenomenon in genetic data, such as gene expression count data. In genetic association studies, it is important to investigate the association between a gene expression and a set of genetic variants from a pathway...
Shameem Alam,Javid Shabbir,Malaika Nadeem
Shameem Alam
Adaptive cluster sampling is particularly helpful whenever the target population is unique, dispersed unevenly, concealed or difficult to find. In the current investigation, under an adaptive cluster sampling approach, we propose a ratio-pr...
Parametric estimation of quantile versions of Zenga and D inequality curves: methodology and application to Weibull distribution [0.03%]
Zenga和D不平等曲线的分位数版本的参数估计：方法论及其在Weibull分布中的应用
Sylwester Pia̧tek
Sylwester Pia̧tek
Inequality (concentration) curves such as Lorenz, Bonferroni, Zenga curves, as well as a new inequality curve - the D curve, are broadly used to analyse inequalities in wealth and income distribution in certain populations. Quantile version...
On the improved estimation of the normal mixture components for longitudinal data [0.03%]
纵向数据正常混合成分估算改进的估计方法研究
Tapio Nummi,Jyrki Möttönen,Pasi Väkeväinen et al.
Tapio Nummi et al.
When analyzing real data sets, statisticians often face the question that the data are heterogeneous and it may not necessarily be possible to model this heterogeneity directly. One natural option in this case is to use the methods based on...
Halima S Twabi,Samuel O M Manda,Dylan S Small et al.
Halima S Twabi et al.
This paper presents a causal inference estimation method for longitudinal observational studies with multiple outcomes. The method uses marginal structural models with inverse probability treatment weights (MSM-IPTWs). In developing the pro...
Gene mutation estimations via mutual information and Ewens sampling based CNN & machine learning algorithms [0.03%]
基于互信息和Ewens抽样CNN及机器学习算法的基因突变估计
Wanyang Dai
Wanyang Dai
We conduct gene mutation rate estimations via developing mutual information and Ewens sampling based convolutional neural network (CNN) and machine learning algorithms. More precisely, we develop a systematic methodology through constructin...
On the use and misuse of time-rescaling to assess the goodness-of-fit of self-exciting temporal point processes [0.03%]
时序点过程的再缩放法使用及其误用以评估自我激发型时间序列点过程拟合优度的方法
M-A El-Aroui
M-A El-Aroui
The paper first highlights important drawbacks and biases related to the common use of time-rescaling to assess the goodness-of-fit (Gof) of self-exciting temporal point process (SETPP) models. Then it presents a new predictive time-rescali...
G Babykina,V Vandewalle,J Carretero-Bravo
G Babykina
Nowadays data are often timestamped, thus, when analysing the events which may occur several times (recurrent events), it is desirable to model the whole dynamics of the counting process rather than to focus on a total number of events. Suc...
Gradient test to assess homogeneity of probabilities in discrete-time transition models with application in agricultural science data [0.03%]
基于农业科学数据的离散时间过渡模型中的概率齐性的梯度检验方法及其应用
Laura Vicuña Torres de Paula,Idemauro Antonio Rodrigues de Lara,Cesar Auguto Taconeli et al.
Laura Vicuña Torres de Paula et al.
Longitudinal studies in discrete or continuous time involving categorical data are common in agricultural sciences. Transition models can be used as a means to analyse the resulting data, especially when the aim is to describe category chan...
Change point detection to analyze air pollution and its economic effects: an exponentially weighted moving average perspective [0.03%]
基于指数权衡移动平均的变点检测及其在空气污染与经济效应分析中的应用
Shabbir Ahmad,Muhammad Riaz,Tahir Mahmood et al.
Shabbir Ahmad et al.
Air pollution has a direct impact on every society, leading to consequential effects on the economy of a nation. Poor air quality adversely affects human health, resulting in various economic outcomes such as rising healthcare costs, dimini...