Fisher information in record data

We present some general results on Fisher information (FI) contained in upper (or lower) record values and associated record times generated from a sequence of i.i.d. continuous variables. For the record data obtained from a random sample of fixed size, we establish an interesting relationship between its FI content and the FI in the data consisting of sequential maxima. We also consider the record data from an inverse sampling plan (Samaniego and Whitaker, 1986). We apply the general results to evaluate the FI in upper as well as lower records data from the exponential distribution for both sampling plans. Further, we discuss the implication of our results to statistical inference from these record data. Received: December 2001 Acknowledgements. This research was supported by Fondo Nacional de Desarrollo Cientifico y Tecnologico (FONDECYT) grants 7990089 and 1010222 of Chile. We would like to thank the Department of Statistics at the University of Concepción for its hospitality during the stay of H. N. Nagaraja in Chile in March of 2000, when the initial work was done. We are grateful to the two referees for various comments that let to improvements in the paper.     

On the Fisher information in record values

In this article, we establish some general results concerning the comparison of the amount of the Fisher information contained in n record values with the Fisher information contained in n iid observations from the original distribution. Some common distributions are classified according to this criterion. We also propose some methods of estimation based on record values. The results may be of interest in some life testing problems. Received: September 1999     

A note on estimation based on record data

In data-processing standpoint, an efficient algorithm for identifying the minimum value among a set of measurements are record statistics. From a sequence of n independent identically distributed continuous random variables only about log(n) records are expected, so we expect to have little data, hence any prior information is welcome (Houchens, Record value theory and inference, Ph.D. thesis, University of California, Riverside, 1984). In this paper, non-Bayesian and Bayesian estimates are derived for the two parameters of the Exponential distribution based on record statistics with respect to the squared error and Linear-Exponential loss functions and then compared with together. The admissibility of some estimators is discussed.     

Inference for the two-parameter bathtub-shaped distribution based on record data

Here we consider the record data from the two-parameter of bathtub-shaped distribution. First, we develop simplified forms for the single moments, variances and covariance of records. These distributional properties are quite useful in obtaining the best linear unbiased estimators of the location and scale parameters which can be included in the model. The estimation of the unknown shape parameters and prediction of the future unobserved records based on some observed ones are discussed. Frequentist and Bayesian analyses are adopted for conducting the estimation and prediction problems. The likelihood method, moment based method, bootstrap methods as well as the Bayesian sampling techniques are applied for the inference problems. The point predictors and credible intervals of future record values based on an informative set of records can be developed. Monte Carlo simulations are performed to compare the so developed methods and one real data set is analyzed for illustrative purposes.     

Extracting information from mega-panels and high-frequency data

With the advent of very large data sets in economics, econometricians, with the help of statisticians, have to re-evaluate current techniques and develop new procedures and their interpretation. Most tests of significance become irrelevant, for example, and conditional distributions become important, but difficult to report. Time series with high frequency data also present new and interesting questions.     

物资信息数据自动采集方式

在物资管理中，数据采集是实现信息处理准确性和及时性的关键，中讨论了物资信息数据的自动采集技术与方式，如条形码技术，。智能卡技术，自动化仪表与传感器技术。     

Global mapping of scientific information exchange using altmetric data

Quality & Quantity - This study seeks to provide new insights into a hidden pattern in the cross-national scholarly network structure from an altmetric perspective. We investigate and visualize...     

Modeling mobile health service delivery to Syrian migrant farm workers using call record data

A significant number of Syrian refugees under temporary protection in Turkey work in agriculture seasonally in various rural areas during several months a year. These migrant farm workers and their families are deprived of access to the regular health care system and preventive services due to their remote locations. The government supports the delivery of different types of mobile health care services, such as vaccination for children, reproductive health and screening services. While planning the mobile health care service delivery, it is critical to know where the refugees will work during what time frame; hence the demand for the services. By analyzing the call record data of a major mobile network operator in Turkey, we quantify the increase in the volume of calls made by Syrian refugees in various agricultural areas during the harvesting season of local crops. This information helps us to forecast spatial and temporal distribution of demand for mobile health care services at a fine granularity. Taking demand over multiple periods as input into a mathematical programming model, we optimize the routing of mobile clinics that visit locations close to where refugees are concentrated over the given planning horizon. We consider three hierarchical objectives. Given the availability of a number of mobile clinics at community health centers in the districts, the first objective aims to maximize the percentage of refugees that can benefit from each service type within pre-defined close distances. The second objective minimizes the number of clinics needed while covering the maximum percentage of refugees. The third objective minimizes the total travel distance of the clinics, while keeping the maximum coverage level using a minimum number of clinics to achieve this level. We quantify the benefits of centralized planning (by the province directorate) over decentralized planning (by each district separately). We also show the trade-off between the required number of clinics and coverage of potential patients.     

How to handle missing data in regression models using information criteria*

An important application of multiple regression is predictor selection. When there are no missing values in the data, information criteria can be used to select predictors. For example, one could apply the small‐sample‐size corrected version of the Akaike information criterion (AIC), the (AICC). In this article, we discuss how information criteria should be calculated when the dependent variable and/or the predictors contain missing values. Therewith, we extensively discuss and evaluate three models that can be employed to deal with the missing data, that is, to predict the missing values. The most complex model, that is, the model with all available predictors, outperforms the other models. These results also apply to more general hypotheses than predictor selection and also to structural equation modeling (SEM) models.     

浅析大数据在高校毕业生就业信息系统中的智能化应用

大数据技术以其全样本分析、多维度描述、交叉验证、非因果相关联系等先进特征,被全世界的先进业态所广泛应用。我国的高校毕业生就业信息系统建设,也应该积极应用大数据技术,来解决目前存在的历史数据沉默、数据库孤岛、依赖随机抽样调查等问题,争取早日实现系统在就业信息推送、就业形势研判以及毕业生就业和培养质量评估等方面的智能化。     

On estimating the median from survey data using multiple auxiliary information

A new method to derive confidence intervals for medians in a finite population is presented. This method uses multi-auxiliary information through a multivariate regression type estimator of the population distribution function. A simulation study based on four real populations shows its behaviour versus other known methods.     

Combining historical and preliminary information to obtain timely time series data

A method is presented to improve the precision of timely data, which are published when final data are not yet available. Explicit statistical formulae, equivalent to Kalman filtering, are derived to combine historical with preliminary information. The application of these formulae is validated by the data, through a statistical test of compatibility between sources of information. A measure of the share of precision of each source of information is also derived. An empirical example with Mexican economic data serves to illustrate the procedure.     

Improving data quality during ERP implementation based on information product map

ABSTRACT

Poor Data Quality (DQ) is amajor culprit in the failure of ERP implantation. Previous DQ solutions focus more on technical approaches, ignoring the importance of seeking the root causes. Therefore, this paper proposes aprocess-driven DQ monitoring framework by Information Product Map (IPMAP). First, IPMAP is applied to visualizethe manufacturing process of critical information products. Then, the potential deficiencies that may arouse DQ problems are examined from the aspects of process and human. Finally, the corresponding DQ improvement strategies are put forward and validated in case study. The results indicate that the framework provides helpful guidance for promoting ERP DQ.     

信息熵在产业结构演变研究中的应用--兼论我国制造业结构演变的时空分异

文章以信息熵作为测度产业结构均衡程度的指标,将其运用于我国制造业结构时空演变特征的实证研究.研究表明我国制造业结构的熵值变化可以分为三个阶段,相应的产业结构演变呈现出"不平衡-平衡-不平衡"的过程;根据我国29个省区制造业结构的演变特征,将全国分为五个类型区;进一步研究发现东部地区制造业结构的均衡程度最高,中部地区最低;在一定范围内制造业结构的均衡程度和区域人口规模的对数呈明显的正相关关系,说明人口规模是影响区域产业结构的因素之一,而且一定范围内城市人口规模越大,各部门发展越均衡.     

Asymptotically efficient recursive estimation for incomplete data models using the observed information

For a recursive maximum-likelihood estimator with step lengths decaying as 1/n, an adaptive matrix needs to be incorporated to obtain asymptotic efficiency. Ideally, this matrix should be chosen as the inverse Fisher information matrix, which is usually very difficult to compute for incomplete data models. In this paper we give conditions under which the observed information can be incorporated into the recursive procedure to yield an efficient estimator, and we also investigate the finite sample properties of these estimators by simulation.     

Recovery of hidden information from stock price data: A semiparametric approach

This paper proposes a new methodology for measuring announcement effect on stock returns. This methodology requires no prior specification of the event day, event, and estimation windows, and therefore is a generalization of the traditional event study methodology. The dummy variable, which indicates whether the event occurred or not, is treated as missing. The unconditional probability of abnormal return is estimated by the EM algorithm. The probability that announcement is effective and the average announcement effect are estimated by the Gibbs sampler. How the method works is demonstrated on simulated data and IBM stock price returns.     

Healthcare information systems: data mining methods in the creation of a clinical recommender system

Recommender systems have been extensively studied to present items, such as movies, music and books that are likely of interest to the user. Researchers have indicated that integrated medical information systems are becoming an essential part of the modern healthcare systems. Such systems have evolved to an integrated enterprise-wide system. In particular, such systems are considered as a type of enterprise information systems or ERP system addressing healthcare industry sector needs. As part of efforts, nursing care plan recommender systems can provide clinical decision support, nursing education, clinical quality control, and serve as a complement to existing practice guidelines. We propose to use correlations among nursing diagnoses, outcomes and interventions to create a recommender system for constructing nursing care plans. In the current study, we used nursing diagnosis data to develop the methodology. Our system utilises a prefix-tree structure common in itemset mining to construct a ranked list of suggested care plan items based on previously-entered items. Unlike common commercial systems, our system makes sequential recommendations based on user interaction, modifying a ranked list of suggested items at each step in care plan construction. We rank items based on traditional association-rule measures such as support and confidence, as well as a novel measure that anticipates which selections might improve the quality of future rankings. Since the multi-step nature of our recommendations presents problems for traditional evaluation measures, we also present a new evaluation method based on average ranking position and use it to test the effectiveness of different recommendation strategies.     

A record linkage system as a means to extensive socio-economic farm population data: 1971 Census of Canada

In this paper, a record linkage system is proposed as a viable technique for tapping vast amounts of potentially useful socio-economic farm population data which presently remain virtually unexploited in the national census data-banks of a good many countries. As an illustrative case, plans for the complete collation of results from Canada's 1971 Census' of Agriculture and Population are outlined, and critical factors in the design of the linkage system to be used are detailed. Throughout the discussion, imperatives for the design of the manual and automated aspects of a pragmatic record linkage system have been raised as guide-lines for analogous linkage applications.     

可口可乐不断提高配送中心作业效率

2008年,德马泰克帮助可口可乐阿马提尔公司(以下简称CCA)位于澳大利亚Eastern Creek市的新配送中心设计并安装了世界领先的订单履行系统.值得一提的是,该配送中心采用了全新的"逆向分货"(Negative-put)系统,平均每小时可完成拣选作业超过1400次,创历史新高,极大地提升了配送中心的订单处理效率,为CCA打造快速反应的供应链提供了技术保障.