Nearest Neighbor Classification Rule for Mixtures of Discrete and Continuous Random Variables

In this paper very simple nonparametric classification rule for mixtures of discrete and continuous random variables is described. It is based on the method of nearest neighbor proposed by Cover and Hart (1967). The bounds on the limit of the nearest neighbor rule risks are given. Both lower and upper bound depend on the Bayes risk and the loss function. Finally the method is compared with other existing methods on some practical data set.     

Isomeric lipid signatures reveal compartmentalized fatty acid metabolism in cancer

The cellular energy and biomass demands of cancer drive a complex dynamic between uptake of extracellular FAs and their de novo synthesis. Given that oxidation of de novo synthesized FAs for energy would result in net-energy loss, there is an implication that FAs from these two sources must have distinct metabolic fates; however, hitherto, all FAs have been considered part of a common pool. To probe potential metabolic partitioning of cellular FAs, cancer cells were supplemented with stable isotope-labeled FAs. Structural analysis of the resulting glycerophospholipids revealed that labeled FAs from uptake were largely incorporated to canonical (sn-) positions on the glycerol backbone. Surprisingly, labeled FA uptake also disrupted canonical isomer patterns of the unlabeled lipidome and induced repartitioning of n-3 and n-6 PUFAs into glycerophospholipid classes. These structural changes support the existence of differences in the metabolic fates of FAs derived from uptake or de novo sources and demonstrate unique signaling and remodeling behaviors usually hidden from conventional lipidomics.     

Robust Selection of the Most Discriminative Variables in the Dichotomous Problem with Application to Some Respiratory Disease Data

A robust method for selection of variables with the greatest discriminatory power is presented in the paper. The method deals with the two groups of data problem. An application of the method to some respiratory disease data and comparisons with classical procedures are given, also.     

Comparing Stochastically Restricted Linear Estimators in a Regression Model

Conditions for superiority of the minimum dispersion estimator over another with respect to the covariance matrix are derived when the vector parameter of a regression model is subject to competing stochastic restrictions. The restrictions may also consist both of a deterministic part and a stochastic part.     

Seemingly Unrelated Generalized Linear Models

By using deviance standardized residuals, the seemingly unrelated regression estimation procedure is extended to generalized linear models, and fitted by an iterative procedure. The matrix of cross products of standardized residuals is asymptotically multivariate normal, and can be used for further multivariate analyses and for hypothesis testing.     

Coexistence of natural enemies in a multitrophic host–parasitoid system

Abstract.  1. This study explored the temporal and spatial aspects of coexistence over many generations in a multispecies host–parasitoid assemblage.
2. The long-term interaction between the cabbage root fly, Delia radicum (Diptera: Anthomyiidae), and two of its natural enemies, Trybliographa rapae (Hymenoptera: Fitigidae) and Aleochara bilineata (Coleoptera: Staphylinidae), in a cultivated field at Silwood Park over 19 years was explored.
3. Although time series showed that the populations were regulated, the impact of the natural enemies was highly variable. Within-year determinants showed that the spatial response of the specialist parasitoid, T. rapae , was predominantly independent of host density while A. bilineata acted simply as a randomly foraging generalist parasitoid.
4. These findings are compared and contrasted with an earlier investigation of the same system when only the first 9 years of the time series were available. This study demonstrated the potential of long-term field studies for exploring hypotheses on population regulation, persistence, and coexistence.     

Progeny testing for recessive genes: procedures and interpretations

Summary Methods for calculating the probability of detecting a carrier of a recessive gene by utilizing matings among related individuals are presented for single and litter bearing species. The confidence level for detection of heterozygosity depends upon: (1) the genetic relationship between mates, (2) the number of mates per male and the number of offspring per mate, (3) whether an estimate of recessive gene frequency before selection is available and (4) the magnitude of that frequency. Methods of computing probability of heterozygosity vs homozygosity utilizing Bayes theorem also are presented. In the conventional progeny test method, a sire initially is assumed heterozygous before calculations are made, but no prior information concerning his probable genotype is utilized. In the method using Bayes theorem, prior sources of information from relatives or from estimates of population allele frequency are utilized. This method gives the exact probability that a sire is not a carrier, given prior information and that he produces all normal offspring. These methods could be used in any sexually reproducing species to identify not only detrimental genes but beneficial genes as well.