Generalized linear mixed models with informative dropouts and missing covariates

Generalized linear mixed models (GLMM) are useful in many longitudinal data analyses. In the presence of informative dropouts and missing covariates, however, standard complete-data methods may not be applicable. In this article, we consider a likelihood method and an approximate method for GLMM with informative dropouts and missing covariates. The methods are implemented by Monte–Carlo EM algorithms combined with Gibbs sampler. The approximate method may lead to inconsistent estimators but is computationally more efficient than the likelihood method. The two methods are evaluated via a simulation study for longitudinal binary data, and appear to perform reasonably well. A dataset on mental distress is analyzed in details.     

Spurious welfare reversals in international business cycle models

Several papers have documented spurious welfare reversals: incomplete-markets economy produces a higher level of welfare than the complete-markets economy. This paper first demonstrates how conventional linearization can generate approximation errors that can result in welfare reversals. Using a two-country production economy, we argue that spurious welfare reversals are not only possible but also plausible under reasonable values for model parameters. This paper then proposes an approximation method that modifies the conventional linearization by a bias correction. This method can be easily implemented and approximates welfare as accurately as a second-order perturbation method.     

A novel modeling approach for the fleet deployment problem within a short-term planning horizon

This paper is concerned with model development for a short-term fleet deployment problem of liner shipping operations. We first present a mixed integer nonlinear programming model in which the optimal vessel speeds for different vessel types on different routes are interpreted as their realistic optimal travel times. We then linearize the proposed nonlinear model and obtain a mixed integer linear programming (MILP) model that can be efficiently solved by a standard mixed integer programming solver such as CPLEX. The MILP model determines the optimal route service frequency pattern and take into account the time window constraints of shipping services. Finally, we report our numerical results and performance of CPLEX on randomly generated instances.     

Mending the family tree a reconciliation of the linearization and levels schools of AGE modelling

This paper offers a critical comparison between the North American levels school of applied general equilibrium modelling, and the Norwegian/Australian school of linearizers. The paper develops both the levels and linearized representations of a neoclassical multiregion trade model. This is used as a vehicle for focusing attention on similarities and differences between the two schools. The main conclusions are: (i) that both the levels and linearized versions of non-linear AGE model offer a valid starting point for obtaining accurate solutions to the non-linear equilibrium problem; (ii) when update formulae are not employed, linearized representations are particularly prone to erroneous welfare conclusions; (iii) the levels representation offers a more natural starting point for expressing accounting conditions, whereas behavioural relationships are relatively more easily expressed in a linearized representation. Recent software developments now make both approaches to the representation and solution of non-linear AGE models convenient to implement. Thus the choice of which approach to use will depend on the special needs and preferences of the economist implementing the model. The two traditions of AGE modelling have a great deal in common and both would benefit from greater cooperation.     

产业生态化与线性化：经济发展模式转型的博弈分析

传统的经济发展模式是资源单向流动的线性化发展模式,短期内可以促进经济发展,但同时也造成环境污染和生态退化,形成人类活动与自然系统的对立与冲突。产业生态化经济发展模式利用自然生态系统原理,从系统观点提出产业的调整,使人类生产系统与自然生态系统充分交融,实现物质反复循环流动,是改变线性化经济发展模式的根本手段,符合建设节约...     

Economic lot and delivery scheduling problem for multi-stage supply chains

The economic lot and delivery scheduling problem for a multi-stage supply chain comprising multiple items is studied in this paper. It is required to develop a synchronized replenishment strategy, and specify the sequence of production and the replenishment cycle time that achieves synchronization through the supply chain at minimum cost. The problem is presented in a novel formulation based on the quadratic assignment representation. The common cycle time and the integer multipliers policies are adopted to accomplish the desired synchronization. The two policies are represented by nonlinear models handled through a hybrid algorithm. The algorithm combines linearization, outer approximation and Benders decomposition techniques. Results of the two policies demonstrate that a cost reduction up to16.3% can be attained by employing the integer multipliers policy instead of the common cycle time. Computational experiments show the efficiency of the new formulation and solution algorithm by reaching the optimal solution for large problem instances in short time.     

功率放大器的自适应预失真线性化技术

重点介绍了几种主要的功率放大器的自适应预失真技术,包括基带预失真、中频预失真及射频预失真技术,以及几种自适应预失真工作函数的产生方法,并利用多项式产生工作函数的方法对功率放大器进行预失真调整,使其线性度得到明显改善。     

带多个变点的逐段连续线性分位数回归模型及应用

研究目标：建立具有多个变点的逐段连续线性分位数回归模型（Continuous Piecewise Linear Quantile Regression with Multiple Change Points,CPLQR）。研究方法：先通过LASSO和广义贝叶斯信息准则确定变点个数,再通过线性化技巧来估计变点的位置与回归系数。研究发现：新方法能够同时确定变点个数、估计变点位置和回归系数,而且具有较强的稳健性;应用该方法于年龄和身体质量指数之间关系,进一步证实了模型的实用性。研究创新：新方法能够处理多个变点的问题,通过LASSO和广义贝叶斯信息准则确定变点数目,避免了主观判断的弊端;借助线性化技巧,解决了目标函数在变点处不可导问题。研究价值：本文结果将为分析经济、金融、医药和生物等学科中存在结构变化的数据提供强有力的研究工具。