在计数数据中的多对线性方面,Ridge-penalized零膨胀的Probit Bell模型用于计数数据的多对线性
Essoham Ali1,2, Adewale F Lukman3
1Institut de Mathématiques Appliquées, UCO, Angers, France.
Journal of applied statistics
|March 16, 2026
概括
本研究为零膨胀试验钟 (ZIPBell) 回归模型引入了一个值估计器. 这种方法提高了复杂计数数据的参数稳定性,即使有相关的预测器.
科学领域:
- 统计 统计 统计 统计
- 计量经济学 计量经济学 计量经济学
- 生物统计学 生物统计学
背景情况:
- 计数数据经常显示过多的零 (结构零) 和潜在的多对线性.
- 现有的模型,如零膨胀钟 (ZIBell) 模型,解决结构零.
- 试点链接函数对于模拟零通胀组件是有效的.
研究的目的:
- 为零膨胀试验钟 (ZIPBell) 回归模型开发一个值估计器.
- 为了稳定ZIPBell模型中的多线性存在的参数估计.
- 为分析具有结构零和相关预测器的复杂计数数据提供强大的方法.
主要方法:
- 为ZIPBell模型开发了一个峰处罚估计器.
- 通过为零通胀部分整合试验链接函数来调整零通胀钟 (ZIBell) 模型.
- 使用脊柱惩罚来减少方差和减轻多线性效应.
主要成果:
- 拟议的山脊估计器在多线性不同水平上显示出强度.
- 该方法有效地稳定了参数估计,而不排除相关预测因素.
- 数学研究和经验应用证实了这种方法对于稀疏和复杂的计数数据的可靠性.
结论:
- 对于ZIPBell模型的峰估计器提供了一个有价值的工具,用于分析具有结构零和多对线性的计数数据.
- 这种方法在具有挑战性的统计场景中提高了参数估计的可靠性.
- 该方法为复杂计数数据分析提供了稳定有效的替代方案.
相关概念视频
Mechanistic Models: Compartment Models in Individual and Population Analysis
318
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
318
Truncation in Survival Analysis
681
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
681
Multiple Regression
4.3K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.3K
Outliers and Influential Points
6.6K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
6.6K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
1.4K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
1.4K
Quantifying and Rejecting Outliers: The Grubbs Test
4.4K
Sometimes, a data set can have a recorded numerical observation that greatly deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier. To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
4.4K


