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Charles Dickens may well have written about baseball's American League East in 2018 that it was the best of teams, it was the worst of teams. This grouping of only [...]

The strikeout is one of the few outcomes ascribed to a pitcher's control, as indicated by metrics such as Fielding Independent Pitching (FIP) and Skill-Interactive Earned Run Average (SIERA). However, [...]

In this paper, within the Italian electricity market, we analyse the features and the dynamics of the imbalance sign, defined as the sign of the algebraic sum of energy bought and sold by the national Transmission and System Operator during the real-time balancing of the electric network. The analyses provide evidence that the probability of having a positive (negative) sign exhibits a serial dependence structure and a dependence on the load periods, as well as on past history. Based on this evidence, we build a suitable model for zonal sign dynamics, and we use it for an out-of-sample forecasting exercise concerning the probability of a positive imbalance sign, [[pi].sub.r] The results show that the zonal imbalance sign is 'predictable.' An economic evaluation of the benefits of using the proposed model is also provided. Keywords: Balancing and ancillary services markets, IPEX market, Zonal imbalance sign, Binary data models, Forecasting, 1. INTRODUCTION: THE RESERVE MARKET IN ITALY The Italian electricity market aims to both promote competition in electricity generation, sale and purchase and ensure the economic management of ancillary services, [...]

This article describes the results of an extensive review of reference transactions from multiple service points at the University of Utah's J. Willard Marriott Library. The review enabled us to better understand the types of questions asked at our service points and resulted in a new set of codes for categorizing reference transactions that focus on recording the kinds of expertise needed to answer each question. We describe the differences between our model and other scales for collecting reference questions. Our method for reviewing reference transactions and developing new codes may be useful to other libraries interested in updating how they collect reference statistics., In this paper we develop a strategy to evaluate public service points in an academic library based on the expertise sought by library patrons. (1) Although there is already an [...]

The Impartial Jury Clause of the Sixth Amendment requires that the venire from which the state and the defendant draw a twelve-person petit jury be a fair cross-section of the [...]

The movement toward the increased use of analytics in organizations has generated much discussion by academics and professionals about the impacts and opportunities that analytics offers. Although operations research (OR) [...]

The oversight of the U.S. Food and Drug Administration (FDA) concerning labeling and promotion of medical products is responsible for the increasing health care expenditures in the U.S. The FDA should hence use statistical tools and comparative effectiveness research for better evaluation of new medicines and treatments.

A novel second-order-statistics-based sequential blind extraction algorithm for blind extraction of quasi-periodic signals, with time-varying period, is introduced in this paper. Source extraction is performed by sequentially converging to a solution that effectively diagonalizes autocorrelation matrices at lags corresponding to the time-varying period, which thereby explicitly exploits a key statistical nonstationary characteristic of the desired source. The algorithm is shown to have fast convergence and yields significant improvement in signal-to-interference ratio as compared to when the algorithm assumes a fixed period. The algorithm is further evaluated on the problem of separation of a heart sound signal from real-world lung sound recordings. Separation results confirm the utility of the introduced approach, and listening tests are employed to further corroborate the results. Index Terms--Blind source extraction (BSE), quasi-periodic, second-order statistics, statistical nonstationarity, time-varying period.

The expanded disability status scale (EDSS) is an ordinal score that measures progression in multiple sclerosis (MS). Progression is defined as reaching EDSS of a certain level (absolute progression) or increasing EDSS by one point (relative progression). Survival methods for time to progression are not adequate for such data because they do not exploit the EDSS level at the end of follow-up. Instead, we suggest a Markov transitional model applicable for repeated categorical or ordinal data. This approach enables derivation of covariate-specific survival curves, obtained after estimation of the regression coefficients and manipulations of the resulting transition matrix. Large-sample theory and resampling methods are employed to derive pointwise confidence intervals, which perform well in simulation. Methods for generating survival curves for time to EDSS of a certain level, time to increase EDSS by at least one point, and time to two consecutive visits with EDSS greater than 3 are described explicitly. The regression models described are easily implemented using standard software packages. Survival curves are obtained from the regression results using packages that support simple matrix calculation. We present and demonstrate our method on data collected at the Partners Multiple Sclerosis Center in Boston. We apply our approach to progression defined by time to two consecutive visits with EDSS greater than 3 and calculate crude (without covariates) and covariate-specific curves. KEY WORDS: Markov model; Multistate model; Ordinal response; Pointwise confidence interval; Survival curve; Time series: Transition model.

High-dimension low-sample size statistical analysis is becoming increasingly important in a wide range of applied contexts. In such situations, the popular support vector machine suffers from 'data piling' at the margin, which can diminish generalizability. This leads naturally to the development of distance-weighted discrimination, which is based on second-order cone programming, a modern computationally intensive optimization method. KEY WORDS: Classification; High-dimension low sample size; Support vector machine.

The support vector machine (SVM) is a powerful method for statistical classification of data used in a number of different applications. However, the usefulness of the method in a commercial available system is very much dependent on whether the SVM classifier can be pretrained from a factory since it is not realistic that the SVM classifier must be trained by the customers themselves before it can be used. This paper proposes a novel SVM classification system for voltage disturbances. The performance of the proposed SVM classifier is investigated when the voltage disturbance data used for training and testing originated from different sources. The data used in the experiments were obtained from both real disturbances recorded in two different power networks and from synthetic data. The experimental results shown high accuracy in classification with training data from one power network and unseen testing data from another. High accuracy was also achieved when the SVM classifier was trained on data from a real power network and test data originated from synthetic data. A lower accuracy resulted when the SVM classifier was trained on synthetic data and test data originated from the power network. Index Terms--Power quality, statistical learning theory, support vector machines, voltage disturbance classification, voltage event.

The analysis of panel data to tro evaluate the government's policy on the encouragement of innnovative research and product development in Argentina is described.

The analysis of the spatial structure of the public transportation utilization in Flanders, Belgium, is presented. The determination of the number of significant flows of traffic, based on the degree of polarization of flow data of the traffic in Flanders, is described.

The derivation of an index of racial segregation in the United States, based on the trends of social interaction among Americans, is presented.

The statistical analysis of the relation between parenting stress and parental materialism in British parents of secondary school students is presented.

The cross-cultural analysis of data, pertaining to the effects of appeals and arguments on consumers in North America and China, is presented.

Results of a direct numerical simulation of a film cooling jet are used to evaluate the terms in the standard k-[epsilon] turbulence model From the direct numerical simulation data all terms and correlations appearing in the exact k-[epsilon] equations are reconstructed and compared with the models for these terms used in the standard k-[epsilon] turbulence model. Unlike a channel flow, the turbulent diffusion terms that contain fluctuations of pressure are found to be significant and to have a different distribution from the turbulent diffusion terms involving only velocity fluctuations. Using an eddy viscosity derived from minimizing the error in representing the direct numerical simulation data by the Boussinesq gradient approximation, it is shown that the Boussinesq gradient approximation as used in the standard k-[epsilon] turbulence model is a reasonable model for the various terms in the exact k-[epsilon] equations. However, the expression for the eddy viscosity of the standard k-[epsilon] turbulence model ([C.sub.[mu]]([k.sup.2]/[epsilon])Re) is shown to be greatly in error. Using the direct numerical simulation data, two new damping functions are presented that greatly reduce the error in the eddy viscosity in the standard k-[epsilon] turbulence model. DOI: 10.2514/1.50597

We describe a novel method for jointly estimating crossing-over and gene-conversion rates from population genetic data using summary statistics. The performance of our method was tested on simulated data sets and compared with the composite-likelihood method of R. R. Hudson. For several realistic parameter values, the new method performed similarly to the composite-likelihood approach for estimating crossing-over rates and better when estimating gene-conversion rates. We used our method to analyze a human data set recently genotyped by Perlegen Sciences.

Many authors have advocated the use of power analysis for designing more sensitive and efficient ecological studies. However, few manuscripts report using power analysis for improving the study design, perhaps [...]

This article reviews power priors, a class of prior distributions for an unknown parameter that exploits information from results of previous, similar studies, a situation arising often in clinical trials. The article shows that, for independent and identically distributed historical data, a basic formulation of power priors (geometric priors) can be obtained as the result of a prior updating-and-combining process based on training samples of iid historical data. This formulation gives an operational justification to power priors. It also allows us to relate the discount scalar quantity controlling the influence of historical information on final inference to the size of training samples. Properties of power priors and their extension to more complex set-ups are discussed. Then several examples are provided of their use in the analysis of clinical trials data. The approach is shown to be appropriate for handling problems arising when information is combined from different studies, such as lack of exchangeability between preceding and current data, and the risk that prior information overwhelms evidence from the study in question. KEY WORDS: Conjugate analysis; Elicitation; Geometric priors; Objective Bayesian analysis; Prediction; Training sample.

The utility of the pure jump process for optimal sampling of high-frequency data, to examine the properties of realized variance of stock prices under alternative sampling schemes, is examined.

The sampling techniques to be used to examine the impact of market microstructure noises on realized variance in high-frequency data on Dow Jones Industrial Average stocks are described.

The evaluation of the model of the relation between market microstructure noise and the realized variance in high-frequency data on Dow Jones Industrial stocks is presented.

The empirical analysis of the impact of market microstructure noise, on the realized variance in high-frequency data on Dow Jones Industrial Average stocks is presented.

The methods of determining the volatility of stock prices, based on the impact of market microstructure noise on the realized variance of high-frequency data from the Dow Jones Industrial Averages, are described.

Based on one observation X from a N([theta], [theta]) distribution where [theta](> 0) is an unknown parameter, this article provides an exact expression of the minimum variance unbiased estimator of [theta] based on the complete and sufficient statistic |X|. Even though N([theta], [theta]) belongs to a one-parameter exponential family, I discuss some small surprises and intricacies that are worth noting. KEY WORDS: Maximum likelihood estimator; Minimum variance; Rao-Blackwellization; Unbiased estimation.

Basketball coaches at all levels use shot charts to study shot locations and outcomes for their own teams as well as upcoming opponents. Shot charts are simple plots of the location and result of each shot taken during a game. Although shot chart data are rapidly increasing in richness and availability, most coaches still use them purely as descriptive summaries. However, a team's ability to defend a certain player could potentially be improved by using shot data to make inferences about the player's tendencies and abilities. This article develops hierarchical spatial models for shot-chart data, which allow for spatially varying effects of covariates. Our spatial models permit differential smoothing of the-fitted surface in two spatial directions, which naturally correspond to polar coordinates: distance to the basket and angle from the line connecting the two baskets. We illustrate our approach using the 2003-2004 shot chart data for Minnesota Timberwolves guard Sam Cassell. KEY WORDS: Bayesian; Conditionally autoregressive prior; Sports.

Social service programs operate in an outcome-driven climate of program service delivery where external funding and regulating bodies demand outcome reporting. Administrative tools are needed to assist with decision-making that aims to improve program services and outcomes. In this article, we present Event History Analysis (EHA) as a statistical tool that can be used to investigate whether particular factors such as client or service characteristics lead to better outcomes in a family preservation program. The authors present a conceptual overview of EHA and discuss its utility as a diagnostic tool for program planning. Additionally, a demonstration of EHA is presented using Statistical Package for the Social Sciences (SPSS) software. The authors also illustrate how EHA can be used to explore program data beyond periodic counts of client outcome success and failure, and make meaningful time-sensitive changes to service delivery. Using three client characteristics that contribute to the risk of abuse: learning disability, family income, and family size, the article discusses the program and practice implications of these variables in working in a family preservation program. The article aims to provide a basic understanding of EHA for social service managers or administrators, since it is quickly becoming a common analytical method in social work research. Equipped with a conceptual understanding of EHA, administrators can direct their program evaluators to conduct EHA on program data. KEYWORDS. Program evaluation, client outcomes, quantitative analysis, statistics, Event History Analysis

A method of developing neural network models for time series that can be used for forecasting is presented. The model uses statistics for computing the forecasts.

A methodical framework incorporating an integrated early warning system, which helps in forecasting failure of banks, is presented. The model uses statistics for analyzing the financial performance of the banks. The model is prepared based on the banks in Turkey.

A number of studies of the motor system suggest that the majority of primary motor cortical neurons represent simple movement-related kinematic and dynamic quantities in their time-varying activity patterns. An example of such an encoding relationship is the cosine tuning of firing rate with respect to the direction of hand motion. We present a systematic development of statistical encoding models for movement-related motor neurons using multielectrode array recordings during a two-dimensional (2-D) continuous pursuit-tracking task. Our approach avoids massive averaging of responses by utilizing 2-D normalized occupancy plots, cascaded linear-nonlinear (LN) system models and a method for describing variability in discrete random systems. We found that the expected firing rate of most movement-related motor neurons is related to the kinematic values by a linear transformation, with a significant nonlinear distortion in about 1/3 of the neurons. The measured variability of the neural responses is markedly non1 Poisson in many neurons and is well captured by a 'normalized-Gaussian' statistical model that is defined and introduced here. The statistical model is seamlessly integrated into a nearly-optimal recursive method for decoding movement from neural responses based on a Sequential Monte Carlo filter. Index Terms--Discrete distribution, LN model, neural decoding, neuroprosthetics, sequential Monte-Carlo.

The electromyographic (EMG) signal provides information about the performance of muscles and nerves. At any instant, the shape of the muscle signal, motor unit action potential (MUAP), is constant unless there is movement of the position of the electrode or biochemical changes in the muscle due to changes in contraction level. The rate of neuron pulses, whose exact times of occurrence are random in nature, is related to the time duration and force of a muscle contraction. The EMG signal can be modeled as the output signal of a filtered impulse process where the neuron firing pulses are assumed to be the input of a system whose transfer function is the motor unit action potential. Representing the neuron pulses as a point process with random times of occurrence, the higher order statistics based system reconstruction algorithm can be applied to the EMG signal to characterize the motor unit action potential. In this paper, we report results from applying a cepstrum of bispectrum based system reconstruction algorithm to real wired-EMG (wEMG) and surface-EMG (sEMG) signals to estimate the appearance of MUAPs in the Rectus Femoris and Vastus Lateralis muscles while the muscles are at rest and in six other contraction positions. It is observed that the appearance of MUAPs estimated from any EMG (wEMG or sEMG) signal clearly shows evidence of motor unit recruitment and crosstalk, if any, due to activity in neighboring muscles. It is also found that the shape of MUAPs remains the same on loading. Index Terms--Electromyographic signals, higher order statistics theory, HOS-based blind deconvolution, motor unit action potential.

The geological profession has only recently become numerically literate but highly so in a relatively short time. Mathematics was applied to geological problems mostly in the fields of hydrology, engineering geology, and geophysics until the past few decades. Statistics were used by sedimentologists and paleontologists to describe populations with some univariate, bivariate, and multivariate statistics used by a few avant garde workers. Geocomputing really started in the 1960s but the slow start became an avalanche in the 1980s with the introduction of microcomputer [personal computer (PC)]. The trend towards increasing quantification of the discipline is noticeable, and in recent years, this trend has been accelerating. There is seemingly no limit to the information and communication revolution. Keywords: Computers; Statistics; Mathematics; Numerical geology

Editor's Note: Research is essential to the health and growth of the statistics discipline. The following article discusses some basic strategies for doing and presenting research based on the authors' experience and conversations with other statisticians. The August 2004 issue of The American Statistician will feature a discussion on the topic 'How to do Statistical Research.' All readers are invited to contribute to this special section. Discussion about this article or general perspectives on being a researcher in the discipline of statistics are welcome. Because of space limitations, we ask that your contribution not exceed 500 words. Articles received by the TAS editorial office (tas@bgnet.bgsu.edu) by June 4, 2004, will be considered for publication.--James Albert, Editor, The American Statistician For new graduate students, we discuss issues and aspects of doing statistical research and provide advice. We answer questions that we had when we were beginners, like 'When do I start?', 'How do I start?', 'How do I find out what has already been done?', 'How do I make progress?', 'How do I finish?', and 'What else can I do?'. KEY WORDS: Finding problems; Identifying literature; Presenting; Reading papers; Writing., 1. INTRODUCTION In an academic environment, where most researchers start, it is easy for the beginner to focus too narrowly on a thesis, a paper in a journal, and/or a [...]