Environment

Abstract

This study surveys the development of collections of foreign-language ethnic newspapers in American libraries and archives since the 1960s. Relying on a review of historical and media studies scholarship as well as library and archival science literature, the article aims to identify the main sources of non-English ethnic newspapers available in the United States and to examine the difficulties such newspapers present for libraries, from older print publications to today’s born-digital media, regarding collection development, bibliographic control, and preservation. After a brief historical survey of the foreign-language ethnic press in the United States, the article analyzes the development of library collections since the 1960s as well as libraries’ efforts to preserve them and improve access to them. It then evaluates the state of digitization and online availability of foreign-language ethnic newspapers and initiates a reflection on the need to collect current print and digital ethnic newspapers.     

Data-driven smooth tests for the extreme value distribution

In this paper we present data-driven smooth tests for the extreme value distribution. These tests are based on a general idea of construction of data-driven smooth tests for composite hypotheses introduced by Inglot, T., Kallenberg, W. C. M. and Ledwina, T. [(1997). Data-driven smooth tests for composite hypotheses. Ann. Statist., 25, 1222–1250] and its modification for location-scale family proposed in Janic-Wróblewska, A. [(2004). Data-driven smooth test for a location-scale family. Statistics, in press]. Results of power simulations show that the newly introduced test performs very well for a wide range of alternatives and is competitive with other commonly used tests for the extreme value distribution.     

Climbing the Electronic Capitol Hill

Abstract

The Information Revolution, particularly evidenced by the Internet, e-mail and online access to government documents, has significantly affected the way Congress conducts business. The author reflects on the changes that he has had to make during his seven years of teaching a course on Congressional Office Operations for the U.S. Department of Agriculture (USDA) Graduate School. Through personal experiences, interviews, and historical perspectives, he describes changes in information resources, constituent communications, and press operations on Capitol Hill and how these changes have affected course content. He also describes how the events of September 11, 2001, and the anthrax mail problem have forced consideration of an electronic Congress. Serials Review 2002; 28:287–294.     

Data-driven smooth test for a location-scale family

A combination of a smooth test statistic and (an approximate) Schwarz's selection rule has been proposed by Inglot, T., Kallenberg, W. C. M. and Ledwina, T. ((1997). Data-driven smooth tests for composite hypotheses. Ann. Statist. 25, 1222–1250) as a solution of a standard goodness-of-fit problem when nuisance parameters are present. In the present paper we modify the above solution in the sense that we propose another analogue of Schwarz's rule and rederive properties of it and the resulting test statistic. To avoid technicalities we restrict our attention to location-scale family and method of moments estimators of its parameters. In a parallel paper [Janic-Wróblewska, A. (2004). Data-driven smooth tests for the extreme value distribution. Statistics, in press] we illustrate an application of our solution and advantages of modification when testing of fit to extreme value distribution.     

Volatility forecasting of financial time series using wavelet based exponential generalized autoregressive conditional heteroscedasticity model

Abstract

An improved forecasting model by merging two different computational models in predicting future volatility was proposed. The model integrates wavelet and EGARCH model where the pre-processing activity based on wavelet transform is performed with de-noising technique to eliminate noise in observed signal. The denoised signal is then feed into EGARCH model to forecast the volatility. The predictive capability of the proposed model is compared with the existing EGARCH model. The results show that the hybrid model has increased the accuracy of forecasting future volatility.     

Prediction intervals for hypergeometric distributions

Abstract

The problem of constructing prediction intervals (PIs) for a future sample from a hypergeometric distribution is addressed. Simple closed-form approximate PIs based on the Wald approach, the joint sampling approach, and a fiducial approach are proposed and compared in terms of coverage probability and precision. Construction of the proposed PIs are illustrated using an example.     

Prediction intervals for growth curves

The growth curve model Y^n×p = A^{n×p ξ mtimes;k}B^k×p+ E^nxp, where Y is an observation matrix, &sigma is a matrix of unknown parameters, A is a known matrix of rank m, B is a known matrix of rank k with 1'= (1, …, 1) as its first row, and the rows of E are independent each distributed as N^p(0,Σ,) is considered. The problem of constructing the prediction intervals for future observations using the above model is considered and approximate intervals assuming different structures on σ are derived. The results are illustrated with several data sets.     

Reviews

Abstract

Heather Baker reviews The no-nonsense guide to leadership, management, and teamwork; Elizabeth Parang reviews Systematic searching: Practical ideas for improving results; Anne Washington reviews Digital preservation in libraries: Preparing for a sustainable future.     

Bayesian prediction of the total time on test using doubly censored rayleigh data

In a Bayesian setting, and on the basis of a doubly censored random sample of failure times drawn from a Rayleigh distribution, Fernandez (2000, Statist. Probab. Lett. , 48 , 393-399) considered the problem of predicting an independent future sample from the same distribution. In this article, we extend his work to include the estimation of the predictive distribution of the total time on test up to a certain failure in a future sample, as well as that of the remaining testing time time until all the items in the original sample have failed. Two examples are used to illustrate the prediction procedure.     

A prediction analysis in a constrained multivariate general linear model with future observations

Abstract

We give a mathematical analysis to some fundamental prediction problems on a constrained multivariate general linear model (CMGLM) with future observations, including the derivation of analytical formulas for calculating the best linear unbiased predictors (BLUPs) of all unknown parameter matrices, and the presentation of many novel and valuable properties of the BLUPs.     

Serials Staffing for the Twenty-First Century and Beyond

Abstract

This article provides an overview of the technical services issues relating to the future of serials staffing, particularly for serials catalogers. Trends in cataloging procedures, technical services reorganizations, and the changing roles of professional and paraprofessional employees affect present and future responsibilities of serials work. The author also examines major technological innovations that have affected staffing needs, including journals in electronic format, vendor-supplied holdings data, automatic generation of bibliographic records, and the potential implications of proposed serials cataloging rule changes on the way in which serials will be managed in libraries. Serials Review 2002; 28:195–200.     

Bayesian estimation and prediction based on generalized Type-II hybrid censored sample

ABSTRACT

In this paper, we consider a general form for the underlying distribution and a general conjugate prior, and develop a general procedure for deriving the maximum likelihood and Bayesian estimators based on an observed generalized Type-II hybrid censored sample. The problems of predicting the future order statistics from the same sample and that from a future sample are also discussed from a Bayesian viewpoint. For the illustration of the developed results, the exponential and Pareto distributions are used as examples. Finally, two numerical examples are presented for illustrating all the inferential procedures developed here.     

Planning the Future of Research Library Collections,the Janus Conference on Research Library Collection: Spring 2006 Update

Abstract

The editors scan approximately 120 journals in all disciplines for reviews of serial publications. Journals published since 2010 were monitored for this installment of Serials Review Index. Suggestions for journals to be included in future columns are welcome.     

Comparison among non parametric prediction intervals of order statistics

Abstract

In this article, we are interested in conducting a comparison study between different non parametric prediction intervals of order statistics from a future sample based on an observed order statistics. Typically, coverage probabilities of well-known non parametric prediction intervals may not reach the preassigned probability levels. Moreover, prediction intervals for predicting future order statistics are no longer available in some cases. For this, we propose different methods involving random indices and fractional order statistics. In each case, we find the optimal prediction intervals. Numerical computations are presented to assess the performances of the so-obtained intervals. Finally, a real-life data set is presented and analyzed for illustrative purposes.     

Minimax prediction in the linear model with a relative squared error

Arnold and Stahlecker (Stat Pap 44:107–115, 2003) considered the prediction of future values of the dependent variable in the linear regression model with a relative squared error and deterministic disturbances. They found an explicit form for a minimax linear affine solution d* of that problem. In the paper we generalize this result proving that the decision rule d* is also minimax when the class D{\mathcal{D}} of possible predictors of the dependent variable is unrestricted. Then we show that d* remains minimax in D{\mathcal{D}} when the disturbances are random with the mean vector zero and the known positive definite covariance matrix.     

Decomposition of Prediction Error in Multilevel Models

ABSTRACT

We present a decomposition of prediction error for the multilevel model in the context of predicting a future observable y _*j in the jth group of a hierarchical dataset. The multilevel prediction rule is used for prediction and the components of prediction error are estimated via a simulation study that spans the various combinations of level-1 (individual) and level-2 (group) sample sizes and different intraclass correlation values. Additionally, analytical results present the increase in predicted mean square error (PMSE) with respect to prediction error bias. The components of prediction error provide information with respect to the cost of parameter estimation versus data imputation for predicting future values in a hierarchical data set. Specifically, the cost of parameter estimation is very small compared to data imputation.     

ZING—Z39.50 International

Abstract

This article discusses ZING (Z39.50 International Next: Generation) and the experimental work occurring within the Z39.50 community, to determine what might become the future generation of the Z39.50 information retrieval protocol. Serials Review 2002; 28:248–250.     

Win-probabilities for comparing two Poisson variables

ABSTRACT

This article considers the problem of choosing between two possible treatments which are each modeled with a Poisson distribution. Win-probabilities are defined as the probabilities that a single potential future observation from one of the treatments will be better than, or at least as good as, a potential future observation from the other treatment. Using historical data from the two treatments, it is shown how estimates and confidence intervals can be constructed for the win-probabilities. Extensions to situations with three or more treatments are also discussed. Some examples and illustrations are provided, and the relationship between this methodology and standard inference procedures on the Poisson parameters is discussed.     

Serials Review Index

Abstract

The editors scan approximately 120 journals in all disciplines for reviews of serial publications. Journals published since Spring 2000 were monitored for this installment of Serials Review Index. Suggestions for journals to be included in future columns are welcome. Serials Review 2003; 29:48–57.     

Serials Review Index

Abstract

The editors scan approximately 120 journals in all disciplines for reviews of serial publications. Journals published since July 2000 were monitored for this installment of Serials Review Index. Suggestions for journals to be included in future columns are welcome. Serials Review 2002; 28:232–239.