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.     

An Efficient Regression Type Estimator in Survey Sampling

For the estimation of population mean in simple random sampling, an efficient regression-type estimator is proposed which is more efficient than the conventional regression estimator and hence than mean per unit estimator, ratio and product estimators and many other estimators proposed by various authors. Some numerical examples are included for illustration.     

Semiparametric Regression in Size-Biased Sampling

Summary .  Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.     

Distinguishing Drift and Selection Empirically: “The Great Snail Debate” of the 1950s

Biologists and philosophers have been extremely pessimistic about the possibility of demonstrating random drift in nature, particularly when it comes to distinguishing random drift from natural selection. However, examination of a historical case – Maxime Lamotte’s study of natural populations of the land snail, Cepaea nemoralis in the 1950s – shows that while some pessimism is warranted, it has been overstated. Indeed, by describing a unique signature for drift and showing that this signature obtained in the populations under study, Lamotte was able to make a good case for a significant role for␣drift. It may be difficult to disentangle the causes of drift and selection acting in a population, but it is not (always) impossible.     

Confidence Intervals for the Risk Ratio in Cohort Studies under Inverse Sampling

Three simple interval estimates for the risk ratio in inverse sampling are considered. The first two interval estimates are derived on the basis of Fieller's Theorem and the delta method with the logarithmic transformation, respectively. The third interval estimate is derived on the basis of an F-test statistic proposed by BENNETT (1981) for testing equal probabilities of a disease between two comparison groups when the disease is rare. To evaluate the performance of these three methods, a Monte Carlo simulation is used to compare the actual coverage probability with the nominal confidence level for each method and to estimate the expected length of the corresponding confidence interval in a variety of situations. On the basis of the results found in the simulation, we have concluded that the method with the logarithmic transformation is either equivalent to or better than the other two methods for all situations considered here.     

Joint multiple quantitative trait loci mapping for allometries of body compositions and metabolic traits to body weights in broiler

In order to map quantitative trait loci (QTLs) for allometries of body compositions and metabolic traits in chicken, we phenotypically characterize the allometric growths of multiple body components and metabolic traits relative to BWs using joint allometric scaling models and then establish random regression models (RRMs) to fit genetic effects of markers and minor polygenes derived from the pedigree on the allometric scalings. Prior to statistically inferring the QTLs for the allometric scalings by solving the RRMs, the LASSO technique is adopted to rapidly shrink most of marker genetic effects to zero. Computer simulation analysis confirms the reliability and adaptability of the so-called LASSO-RRM mapping method. In the F₂ population constructed by multiple families, we formulate two joint allometric scaling models of body compositions and metabolic traits, in which six of nine body compositions are tested as significant, while six of eight metabolic traits are as significant. For body compositions, a total of 14 QTLs, of which 9 dominant, were detected to be associated with the allometric scalings of drumstick, fat, heart, shank, liver and spleen to BWs; while for metabolic traits, a total of 19 QTLs also including 9 dominant be responsible for the allometries of T4, IGFI, IGFII, GLC, INS, IGR to BWs. The detectable QTLs or highly linked markers can be used to regulate relative growths of the body components and metabolic traits to BWs in marker-assisted breeding of chickens.     

Effect of feeding boxes on the behavior of stereotyping amur tigers (Panthera tigris altaica) in the Zurich Zoo,Zurich, Switzerland

The stereotyped pacing shown by the two Amur tigers in the Zurich Zoo was hypothesized as being caused by permanently frustrated appetitive foraging behavior. Several electrically controlled feeding boxes were installed and access to each box was possible only twice a day for 15 min at semi‐random times. The boxes had to be opened actively by the tigers. Two trials were carried out: one with solitary confinement, and one with paired confinement. During box feeding, the female's stereotyped pacing was significantly reduced from 16% (solitary confinement, conventional feeding) and 7% (paired confinement, conventional feeding) to 1% (solitary confinement) and less than 0.01% (paired confinement) of the daily observed time. The female's sleeping increased significantly in both solitary and paired confinement. The male only showed a significant reduction in stereotyped pacing behavior when kept with the female (conventional feeding: 10%; box feeding: <0.01% of the daily observed time). On days with a box‐feeding regime in paired confinement, the male spent 25% (83 min) of the observed time with active behavior at the feeding boxes. The results support the hypothesis that permanently frustrated appetitive foraging behavior causes stereotyped pacing in adult tigers. Zoo Biol 21:573–584, 2002. © 2002 Wiley‐Liss, Inc.     

Does Mother Nature really prefer rare species or are log‐left‐skewed SADs a sampling artefact?

Intensively sampled species abundance distributions (SADs) show left‐skew on a log scale. That is, there are too many rare species to fit a lognormal distribution. I propose that this log‐left‐skew might be a sampling artefact. Monte Carlo simulations show that taking progressively larger samples from a log‐unskewed distribution (such as the lognormal) causes log‐skew to decrease asymptotically (move towards ?∞) until it reaches the level of the underlying distribution (zero in this case). In contrast, accumulating certain types of repeated small samples results in a log‐skew that becomes progressively more log‐left‐skewed to a level well beyond the underlying distribution. These repeated samples correspond to samples from the same site over many years or from many sites in 1 year. Data from empirical datasets show that log‐skew generally goes from positive (right‐skewed) to negative (left‐skewed) as the number of temporally or spatially replicated samples increases. This suggests caution when interpreting log‐left‐skew as a pattern that needs biological interpretation.