Direct Modelling of Regression Effects for Transition Probabilities in Multistate Models

Abstract.  A simple and standard approach for analysing multistate model data is to model all transition intensities and then compute a summary measure such as the transition probabilities based on this. This approach is relatively simple to implement but it is difficult to see what the covariate effects are on the scale of interest. In this paper, we consider an alternative approach that directly models the covariate effects on transition probabilities in multistate models. Our new approach is based on binomial modelling and inverse probability of censoring weighting techniques and is very simple to implement by standard software. We show how to do flexible regression models with possibly time-varying covariate effects.     

Regression Analysis of Bivariate Current Status Data Using a Multistate Model

We consider bivariate current status data with death which often occur in animal tumorigenicity experiments. Instead of observing exact tumor onset time, the existence of tumor is known at death time or sacrifice time. Such an incomplete data structure makes it difficult to investigate the effect of treatment on tumor onset times. Furthermore, when tumor onsets occur at two sites, information for the order of their onsets is unknown. A multistate model is applied to incorporate the sequential occurrence of events. For the inference of parameters, an EM algorithm is applied and a real NTP (National Toxicology Program) dataset is analyzed as an illustrative example.     

A Novel Estimation Approach for Mixture Transition Distribution Model in High-Order Markov Chains

A transformation is proposed to convert the nonlinear constraints of the parameters in the mixture transition distribution (MTD) model into box-constraints. The proposed transformation removes the difficulties associated with the maximum likelihood estimation (MLE) process in the MTD modeling so that the MLEs of the parameters can be easily obtained via a hybrid algorithm from the evolutionary algorithms and/or quasi-Newton algorithms for global optimization. Simulation studies are conducted to demonstrate MTD modeling by the proposed novel approach through a global search algorithm in R environment. Finally, the proposed approach is used for the MTD modelings of three real data sets.     

The Optimal Preventive Maintenance Policy for the Multistate System Profit

Here, the problem of preventive maintenance optimization for the multistate system is investigated considering a three-state system. The optimal numbers of preventive maintenance that maximize the expected profit values of this system are evaluated and these numbers are then used to increase the three-state system availability.     

Confidence Bands for Comparison of Transition Probabilities in a Markov Chain Model

We consider graphs, confidence procedures and tests that can be used to compare transition probabilities in a Markov chain model with intensities specified by a Cox proportional hazard model. Under assumptions of this model, the regression coefficients provide information about the relative risks of covariates in one–step transitions, however, they cannot in general be used to to assess whether or not the covariates have a beneficial or detrimental effect on the endpoint events. To alleviate this problem, we consider graphical tests based on confidence procedures for a generalized Q–Q plot and for the difference between transition probabilities. The procedures are illustrated using data of the International Bone Marrow Transplant Registry.     

The Very Model of a Minor/Major Change: A Current Look at Serials Cataloging Title Change Rules

Abstract

This article provides serials professionals with explanations and examples of rules for minor and major changes in the 2002 revision of Anglo-American Cataloguing Rules, 2nd ed. (AACR2), as applied to serials. The authors outline minor/major rules and Library of Congress Rule Interpretations (LCRIs) and give examples for each rule. They also discuss initiatives and meetings leading up to these changes and provide key definitions as well as explore various problems with AACR2 and the intended goals for the revision. Additional discussion focuses on the impact of the minor/major changes on areas such as workflow in technical services, shelving, binding, and training.     

An Efficient Operator for the Change Point Estimation in Partial Spline Model

In bioinformatics application, the estimation of the starting and ending points of drop-down in the longitudinal data is important. One possible approach to estimate such change times is to use the partial spline model with change points. In order to use estimate change time, the minimum operator in terms of a smoothing parameter has been widely used, but we showed that the minimum operator causes large MSE of change point estimates. In this paper, we proposed the summation operator in terms of a smoothing parameter, and our simulation study showed that the summation operator gives smaller MSE for estimated change points than the minimum one. We also applied the proposed approach to the experiment data, blood flow during photodynamic cancer therapy.     

基于转移概率矩阵的企业债券定价模型

企业债券评估的主要方法为结构化风险模型和密度式风险模型,但中国企业债券市场评级数据少、缺乏历史违约事件,因此可以通过对JLT模型进行改进,以加权平均的方式计算经验转移概率矩阵,然后利用市场上各评级债券的时间序列数据计算风险中性违约概率,并通过市场宏观数据判断经济处于上升期还是衰退期,据此计算条件转移概率矩阵,最后通过债券远期折现的方式构建适合中国市场特色的债券定价模型。实证部分选取了2014年部分新发行债券对模型进行了实证检验,并对国内企业债券定价的现状进行了分析。     

Change Point Detection in The Skew-Normal Model Parameters

Bayesian inference under the skew-normal family of distributions is discussed using an arbitrary proper prior for the skewness parameter. In particular, we review some results when a skew-normal prior distribution is considered. Considering this particular prior, we provide a stochastic representation of the posterior of the skewness parameter. Moreover, we obtain analytical expressions for the posterior mean and variance of the skewness parameter. The ultimate goal is to consider these results to one change point identification in the parameters of the location-scale skew-normal model. Some Latin American emerging market datasets are used to illustrate the methodology developed in this work.     

Multistate survival models for transitions and reverse transitions: an application to contraceptive use data

This paper extends the use of the multistate proportional hazards model proposed by R. Kay for transitions, reverse transitions, and repeated transitions. A simple method of testing the equality of vectors of parameters for transitions and repeated transitions is also shown in addition to estimates for the underlying cumulative hazards for different types of transition. The multistate survival models applied to contraceptive use data collected by the International Center for Diarrheal Disease Research, Bangladesh, for the period January 1978 to December 1982 provide useful findings relating to interstate transitions. The author stresses the need to not treat separately states of contraceptive use given their link to the acceptance of the first method, transitions from one method to another, first method discontinuation, periods of non-use, the use of subsequent methods, loss to follow-up, the use of irreversible methods, and subsequent periods of non-use. Religion is an important indicator for the acceptance of an irreversible method as a first or subsequent method; compared to women of other religions, Muslims were less likely to accept an irreversible method as a first or subsequent method. Religion is not, however, associated with the acceptance or subsequent use of a reversible method or with discontinuation of a reversible method. Higher age in the study area is associated with both lower acceptance and longer continuation of a method. Women with a larger number of living sons tend to accept their first method and subsequent methods at an higher rate than women with fewer or no sons. As for educational status, women with higher education proved to be serious users of contraception, although women with less or no education tend to accept an irreversible method at an higher rate than the women with an higher level of education. Further, the desire for more children is a strong predictor for non-use of a method even if contraception is used to space births. The score test suggested in the paper for testing the equality of parameters in models 1-4 reveals that there is no significant difference in the parameters of the models. This paper shows that the factors which affect the acceptance of any reversible method of contraception are different from those for an irreversible method. Moreover, the factors which affect a transition differ from those for a reverse transition in the case of adopting reversible methods.     

A Model for Water Pricing

This note describes a situation in which a simple mathematical model helped solve an important practical problem: how to price water fairly. It is intended as an example, rather than as a mathematical contribution to control theory.     

空间滞后面板平滑转换模型的估计及数值模拟

将空间滞后项引入面板平滑转换模型,构建了空间滞后面板平滑转换模型,通过综合应用拟极大似然法和非线性最小二乘法,构造了该模型的参数估计方法,并通过蒙特卡洛数值模拟探讨了参数估计方法的小样本性质;数值模拟结果显示,提出的估计方法在小样本条件下表现良好,参数估计值随着样本容量的增大而收敛到参数的真值。     

1992-2002年中国产业结构的变化——基于列标尺量模型的分析

 摘　　要:为测定国民经济产业结构的变动，本文创建了一个基于投入产出技术的列标尺量模型。它将部门的结构系数变动分为直接产品消耗系数的变动和增加值结构系数的变动。该模型对中国1992-2002年间部门结构变动作了计算分析，主要结论是这一阶段我国经济结构变动中，农业、煤炭采选业、石油加工和天然气开采业、化学工业、金属制品业、交通运输设备制造业、电子及通信设备制造业及商业饮食业的主要影响因素是增加值结构系数的变动，但直接产品消耗系数对其他工业、建筑业、食品制造和烟草加工及其他社会服务业的影响也逐渐显著，列标尺量模型的提出为产业的规划调整提供了有效的参考依据。     

Robust Estimation of a Spatiotemporal Model with Structural Change

A spatiotemporal model is postulated and estimated using a procedure that infuses the forward search algorithm and maximum likelihood estimation into the backfitting framework. The forward search algorithm filters the effect of temporary structural change in the estimation of covariate and spatial parameters. Simulation studies illustrate capability of the method in producing robust estimates of the parameters even in the presence of structural change. The method provides good model fit even for small sample sizes in short time series data and good predictions for a wide range of lengths of contamination periods and levels of severity of contamination.     

Bivariate Longitudinal Model for Detecting Prescribing Change in Two Drugs Simultaneously with Correlated Errors

Bivariate responses of repeated measures data are usually analysed as two separate responses in the literature by several authors. The two responses usually tend to be related in some way and analysing this data jointly presents an opportunity to account for the joint movement, which may impact on the conclusions reached compared to analysing the responses separately. In this paper, a bivariate regression model with random effects (linear mixed model) is used to detect a change if any in the prescribing habits in the UK at the general practice (family medicine) level due to an educational intervention given repeated measures data before and after the intervention and a control group. The message was to increase the prescribing of one drug while simultaneously decreasing the prescribing of another. The effects of modelling a bivariate auto-regressive process are evaluated.     

平滑转换自回归模型的单位根检验问题研究

 内容提要：针对非线性模型的单位根检验中存在的问题,本文认为非线性模型的单位根检验不应该在AR模型中进行,而应该在非线性模型中进行。以LSTAR(1)模型为例,本文给出了在其中进行单位根检验的统计量及其临界值。用蒙特卡洛试验证实,本文提出的单位根检验统计量的功效明显高于DF单位根检验,只有当非平稳特征十分明显时,DF检验才能检测出其中的单位根,因此,在非线性模型中进行单位根检验是必要的。     

A Semiparametric Model for Recapture Experiments

Abstract. A two-step procedure based on the conditional likelihood is proposed to estimate the population size of a closed population using a semiparametric model for recapture studies. An asymptotic variance estimate and numerical results are presented. The method is applied to a bird banding dataset in Hong Kong.     

A Spatiotemporal Model for Pollutant Concentrations

ABSTRACT

Contamination of underground water tables can be characterized by measurements that are mixtures of short-term spiking, long-term decline, and steady-state variations in contaminant levels. Classical statistical models often fail to capture the changes in contaminant flow because they rely on fitting smooth spatial and temporal functions across the region, smooth functions that might not comprehensively characterize contaminant change. In this article, a more comprehensive approach is presented for modeling such processes. This approach uses a new class of spatiotemporal models that can characterize a broad range of environmental processes. It also effectively uses Bayesian hierarchical model fitting and a novel use of near neighbors to model contamination in an underground water table.     

有计划商品经济条件下的价格变动影响模型

一、问题的提出在商品货币关系的条件下,某一部门价格的变动必然会使其他部门的价格、生产成本乃至利润产生一系列的连锁反映。这种连锁反应,既有直接影响,又有一系列间接影响。因此,为了制订合适配套的调价方案,很有必要事先对调价有可能产生的影响进行测算。