A general algorithm for computing simultaneous prediction intervals for the (log)-location-scale family of distributions

Making predictions of future realized values of random variables based on currently available data is a frequent task in statistical applications. In some applications, the interest is to obtain a two-sided simultaneous prediction interval (SPI) to contain at least k out of m future observations with a certain confidence level based on n previous observations from the same distribution. A closely related problem is to obtain a one-sided upper (or lower) simultaneous prediction bound (SPB) to exceed (or be exceeded) by at least k out of m future observations. In this paper, we provide a general approach for computing SPIs and SPBs based on data from a particular member of the (log)-location-scale family of distributions with complete or right censored data. The proposed simulation-based procedure can provide exact coverage probability for complete and Type II censored data. For Type I censored data, our simulation results show that our procedure provides satisfactory results in small samples. We use three applications to illustrate the proposed simultaneous prediction intervals and bounds.     

Asymptotic confidence intervals in ridge regression based on the Edgeworth expansion

Ridge Regression techniques have been found useful to reduce mean square errors of parameter estimates when multicollinearity is present. But the usefulness of the method rest not only upon its ability to produce good parameter estimates, with smaller mean squared error than Ordinary Least Squares, but also on having reasonable inferential procedures. The aim of this paper is to develop asymptotic confidence intervals for the model parameters based on Ridge Regression estimates and the Edgeworth expansion. Some simulation experiments are carried out to compare these confidence intervals with those obtained from the application of Ordinary Least Squares. Also, an example will be provided based on the well known data set of Hald.     

A note on the moments of stochastic shrinkage parameters in ridge regression

The purpose of this note is to gain insight on the performance of two well known operational Ridge Regression estimators by deriving the moments of their stochastic shrinkage parameters. We also show that, under certain conditions, one of them has bounded moments.     

Bayesian Random Segmentation Models to Identify Shared Copy Number Aberrations for Array CGH Data

Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. We propose a hierarchical Bayesian random segmentation approach for modeling aCGH data that utilizes information across arrays from a common population to yield segments of shared copy number changes. These changes characterize the underlying population and allow us to compare different population aCGH profiles to assess which regions of the genome have differential alterations. Our method, referred to as BDSAcgh (Bayesian Detection of Shared Aberrations in aCGH), is based on a unified Bayesian hierarchical model that allows us to obtain probabilities of alteration states as well as probabilities of differential alteration that correspond to local false discovery rates. We evaluate the operating characteristics of our method via simulations and an application using a lung cancer aCGH data set.     

“Shelf-Ready” Print Serials Acquisitions

The focus of this installment of “The Balance Point” is “shelf-ready” print serials acquisitions, including functions associated with traditional consolidation services (ordering, receiving, check-in, labeling, claiming and batch shipments), and the newer capabilities of uploading check-in data automatically into library systems. Featured authors discuss traditional vendor consolidation services, pilot projects and experiments in the pursuit of what they define as genuinely “shelf-ready” periodicals. The authors view obtaining “shelf-ready” print journal issues as an effective and efficient means of managing print serials operations while coping with the demands of managing digital resource acquisitions with limited financial resources.     

Criminal history and assault of dating partners: the role of type of prior crime, age of onset, and gender

Some studies of assaults on intimate partners have found that most of the perpetrators are not violent outside the family, which suggests a specialized type of crime. However, other studies found domestic violence offenders tend to have extensive criminal histories. To further investigate the extent to which partner assaults are part of a more general pattern of criminal behavior or a specialized type of crime, we studied the dating relationships of 653 university students. Thirty-one percent reported assaulting a partner in the previous 12 months. The rate of assault on partners by females did not differ significantly for males (29%) and females (32%). We also found high rates of other self-reported crime, and much higher rates by males. For example, over one half of the male students and almost one third of the female students reported having stolen money. The male students reported an average of 3.4 crimes committed, and the female students an average of 1.4 crimes. These high crime rates and gender differences are consistent with many previous studies. Logistic regression analysis revealed that a history of prior criminal acts is associated with an increased probability of assaulting a partner. The relationship was greater when there was prior violent crime compared to property crime, when there was early onset of criminal behavior, and when the offender was female. The implications of the findings for understanding partner assaults, criminal careers, and gender differences in the etiology of violence against intimate partners are discussed.     

20 Questions of Gamblers Anonymous: A Psychometric Study with Population of Spain

The authors present a psychometric study of the questionnaire proposed by the Gamblers Anonymous organization for the self-assessment of problem gambling. The study was carried out in Spain with two samples: one of 127 problem gamblers (mean age: 41.67; sex: 78.7% men; mean duration of the problem: 5 years) and the other of 142 social gamblers (mean age: 38.46; sex: 60% men). The questionnaire was self-applied, in the presence of one of the investigators in case any doubts arose. The results indicate that it is a good screening instrument, with high reliability (Cronbach's alpha = 0.94), good covergent validity (the correlation with the SOGS questionnaire is high (r = 0.94; p < 0.001)), good factorial validity (the questionnaire's structure is unidimensional and coherent (just one factor explains more than 50% of the variance)), and its discriminative power is high (diagnostic efficacy = 98.88%). The study offers a comparative analysis of this instrument with other measures of problem gambling, emphasizing its extraordinary performance.     

Fractional integration and impulse responses: a bivariate application to real output in the USA and four Scandinavian countries

This article analyzes impulse response functions in the context of vector fractionally integrated time series. We derive analytically the restrictions required to identify the structural-form system. As an illustration of the recommended procedure, we carry out an empirical application based on a bivariate system including real output in the USA and, in turn, in one of the four Scandinavian countries (Denmark, Finland, Norway, and Sweden). The empirical results appear to be sensitive, to some extent, to the specification of the stochastic process driving the disturbances, but generally a positive shock to US output has a positive effect on the Scandinavian countries, which tend to disappear in the long run.     

A step-by-step algorithm for combining diagnostic tests

Combining data of several tests or markers for the classification of patients according to their health status for assigning better treatments is a major issue in the study of diseases such as cancer. In order to tackle this problem, several approaches have been proposed in the literature. In this paper, a step-by-step algorithm for estimating the parameters of a linear classifier that combines several measures is considered. The optimization criterion is to maximize the area under the receiver operating characteristic curve. The algorithm is applied to different simulated data sets and its performance is evaluated. Finally, the method is illustrated with a prostate cancer staging database.     

Urban risks due to climate change in the Andean municipality of Pasto,Colombia: A Bayesian network approach

The current trends of climate change will increase people's exposure to urban risks related to events such as landslides, floods, forest fires, food production, health, and water availability, which are stochastic and very localized in nature. This research uses a Bayesian network (BN) approach to analyze the intensity of such urban risks for the Andean municipality of Pasto, Colombia, under climate change scenarios. The stochastic BN model is linked to correlational models and local scenarios of representative concentration trajectories (RCP) to project the possible risks to which the municipality of Pasto will be exposed in the future. The results show significant risks in crop yields, food security, water availability and disaster risks, but no significant risks on the incidence of acute diarrheal diseases (ADD) and acute respiratory infections (ARI), whereas positive outcomes are likely to occur in livestock production, influenced by population growth. The advantage of the BN approach is the possibility of updating beliefs in the probabilities of occurrence of events, especially in developing, intermediate cities with information-limited contexts.