Residents,recreationists, ridge regression,and revenues:the five r's of florida's motor- tax

Ridge regression is applied to the question of how to revise Florida's motor-fuel tax to remedy the shortfall of its transportation revenues. Along the way a model of gasoline consumption by residents and tourists is presented, and the differences in consumption patterns between the two types of purchasers are reported.     

Regression methods for high dimensional multicollinear data

To compare their performance on high dimensional data, several regression methods are applied to data sets in which the number of exploratory variables greatly exceeds the sample sizes. The methods are stepwise regression, principal components regression, two forms of latent root regression, partial least squares, and a new method developed here. The data are four sample sets for which near infrared reflectance spectra have been determined and the regression methods use the spectra to estimate the concentration of various chemical constituents, the latter having been determined by standard chemical analysis. Thirty-two regression equations are estimated using each method and their performances are evaluated using validation data sets. Although it is the most widely used, stepwise regression was decidedly poorer than the other methods considered. Differences between the latter were small with partial least squares performing slightly better than other methods under all criteria examined, albeit not by a statistically significant amount.     

Bayesian prediction for small areas using sur models

Sample surveys are usually designed and analyzed to produce estimates for larger areas and/or populations. Nevertheless, sample sizes are often not large enough to give adequate precision for small area estimates of interest. To circumvent such difficulties, borrowing strength from related small areas via modeling becomes essential. In line with this, we propose a hierarchical multivariate Bayes prediction method for small area estimation based on the seemingly unrelated regressions (SUR) model. The performance of the proposed method was evaluated through simulation studies.     

An implicit function based procedure for analyzing maximum likelihood estimates from nonidentically distributed data

A methodology is presented for gaining insight into properties — such as outlier influence, bias, and width of confidence intervals — of maximum likelihood estimates from nonidentically distributed Gaussian data. The methodology is based on an application of the implicit function theorem to derive an approximation to the maximum likelihood estimator. This approximation, unlike the maximum likelihood estimator, is expressed in closed form and thus it can be used in lieu of costly Monte Carlo simulation to study the properties of the maximum likelihood estimator.     

Book review

State-Space Models with Regime Switching by Chang-Jin Kim and Charles R. Nelson. Pp. 250. Cambridge, Massachnsetts: MIT Press, 1999. ($40.00 cloth) WEB INFOR~UATION: http://mitpress.mit.edu/book-home.tcl?isbn=0262l123.     

Bunk Bed Injuries in College Students

Abstract

We surveyed 1,431 college seniors to investigate the frequency and severity of injury after falls from bed. This data was analyzed along with data obtained from both the Consumer Product Safety Commission and the armed forces. We found that falls from bed are common in young adults and that injuries are more likely to occur with falls from bunk or loft beds than from standard beds (p = 0.025). Falls were most common when students were climbing out of bed or were startled awake. Alcohol use was implicated in 36% of the falls. We recommend that the heights of nonstandard beds for students be lowered, that alarms and phones be placed within easy reach, and that sturdy, fixed devices be used to descend. Intoxicated individuals should be placed on standard beds or lower.