Inferences on the mean of zero-inflated lognormal data: the generalized variable approach

2005 ◽  
Vol 24 (20) ◽  
pp. 3223-3232 ◽  
Author(s):  
Lili Tian
Author(s):  
Sanju Scaria ◽  
Seemon Thomas ◽  
Sibil Jose

The article focuses on the inference of stress-strength reliability in generalized Pareto model using the generalized variable approach and bootstrap percentile method. Simulation studies are conducted to obtain expected lengths and coverage probabilities of confidence intervals constructed using the generalized variable and the bootstrap percentile methods. An example consisting of real stress-strength data is also presented for illustrative purposes.


1986 ◽  
Vol 32 (112) ◽  
pp. 434-438 ◽  
Author(s):  
A. C. Hansen ◽  
R. L. Brown

AbstractA statistical model characterizing the granular structure of snow is developed using quantitative stereology. The model is based on specific parameters (e.g. bond radius, grain-size, etc.) which take the form of internal-state variables in a constitutive theory for high-rate deformation of snow. In addition to parameters developed by other authors in previous investigations, a new parameter characterizing the mean bond length is developed. More significantly, general relations are derived for the mean number of bonds per grain and mean number of grains per unit volume without making any assumptions regarding the shape or size of the ice grains, or their respective distributions.


1986 ◽  
Vol 32 (112) ◽  
pp. 434-438 ◽  
Author(s):  
A. C. Hansen ◽  
R. L. Brown

AbstractA statistical model characterizing the granular structure of snow is developed using quantitative stereology. The model is based on specific parameters (e.g. bond radius, grain-size, etc.) which take the form of internal-state variables in a constitutive theory for high-rate deformation of snow. In addition to parameters developed by other authors in previous investigations, a new parameter characterizing the mean bond length is developed. More significantly, general relations are derived for the mean number of bonds per grain and mean number of grains per unit volume without making any assumptions regarding the shape or size of the ice grains, or their respective distributions.


2020 ◽  
pp. jech-2020-213897
Author(s):  
Sotiris Vandoros ◽  
Xiangpu Gong ◽  
Ichiro Kawachi

BackgroundUnemployment has been associated with chronic pain, which is often treated with prescription opioids. Opioid mortality has been included in the so-called category of ‘deaths of despair’ due to the role of lack of opportunity. While previous studies have found an association between unemployment and opioids, the relationship is endogenous and examining any effect is challenging.ObjectiveThe objective of this paper is to study the association between unemployment and opioid prescribing in England.Data and MethodsWe used data from the GP prescribing database in England for the period 2011–2017 and followed ordinary least squares (OLS) and Instrumental Variable econometric approaches, controlling for other confounders. We used the number of foreign direct investment projects and the number of registered companies as instruments for unemployment, taking population size into account.ResultsThe OLS model suggests that an increase in the unemployment rate by 1 percentage point is associated with 0.017 additional opioid defined daily doses per capita—a 0.9% increase compared with the mean of 1.745. According to the instrumental variable model, an increase in unemployment by 1 percentage point leads to an increase in the number of opioid doses prescribed per capita by between 0.315 and 0.437, which constitutes a 18–25% increase compared with the mean of 1.745.ConclusionsUnemployment appears to have an impact on opioid prescribing volume in England. This reveals yet another negative effect of unemployment on health. Relevant labour market policies may play a protective role with regards to opioid use.


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