The authors develop a new class of distributions by introducing skewness in multivariate elliptically symmetric distributions. The class, which is obtained by using transformation and conditioning, contains many standard families including the multivariate skew-normal and t distributions. The authors obtain analytical forms of the densities and study distributional properties. They give practical applications in Bayesian regression models and results on the existence of the posterior distributions and moments under improper priors for the regression coefficients. They illustrate their methods using practical examples. Une nouvelle classe de lois multivariws asymetriques et ses applications dans le cadre de modeles de rhression bayesiensR6ssud : Les auteurs engendrent une nouvelle classe de lois en introduisant un facteur d'asymttrie dans la famille des distributions multivarites elliptiquement symttriques. La classe, qui est obtenue par transformation et conditionnement, inclut plusieurs familles de lois connues, dont la Student et la normale multivarites asymttriques. Les auteurs donnent la forme explicite de la densitk de ces lois et en examinent les proprittks. Ils en pdsentent des applications pratiques dans le cadre des modkles de dgression baytsiens, oh ils dtmontrent l'existence de lois a posteriori et de leurs moments lorsque les lois a priori des paramktres de la dgression sont impropres. ns illustrent en outre leurs mtthodes dans des cas concrets. SAHU, DEY& BRANCO Vol. 31, No. 2 g(u; k, .I.

Molecular markers derived from PCR amplification of genomic DNA are an important part of the toolkit of evolutionary geneticists. RAPDs, AFLPs, and ISSR polymorphisms allow analysis of species for which prior DNA sequence information is lacking, but dominance makes it impossible to apply standard techniques to calculate F -statistics. We describe a Bayesian method that allows direct estimates of F st from dominant markers. In contrast to existing alternatives, we do not assume prior knowledge of the degree of within-population inbreeding. In particular, we do not assume that genotypes within populations are in Hardy-Weinberg proportions. Our estimate of F st incorporates uncertainty about the magnitude of within-population inbreeding. Simulations show that samples from even a relatively small number of loci and populations produce reliable estimates of F st . Moreover, some information about the degree of within population inbreeding (F is ) is available from data sets with a large number of loci and populations. We illustrate 1 the method with a reanalysis of RAPD data from 14 populations of a North American orchid, Platanthera leucophaea.

This paper proposes a general class of multivariate skew-elliptical distributions. We extend earlier results on the so-called multivariate skew-normal distribution. This family of distributions contains the multivariate normal, Student's t, exponential power, and Pearson type II, but with an extra parameter to regulate skewness. We also obtain the moment generating functions and study some distributional properties. Several examples are provided. Academic PressAMS 1991 subject classifications: 60E05; 62H10.

The covariance matrix formula of the multivariate skew-t distribution for non-null δ was wrong as given on page 137, vol. 31 (2003). The correct expression is:As a result of this correction we now state that in the case of the multivariate skew-t distribution with non-null δ the components will always be correlated. Nothing else changes in the paper since hierarchical Bayesian modelling and its MCMC based computation in Section 5 are performed using the distributional specification and not using their moments.The moment generating function given as Lemma A.3 in the Appendix (page 147) does imply the correct covariance matrix as shown below. The moment generating function has been stated as:where G(w) denotes the cumulative distribution function of (ν/2, ν/2). Note that when W ∼To calculate the covariance we want to evaluateStraightforward calculation yields the following:

Multiplexed biomarker protein detection holds unrealized promise for clinical cancer diagnostics due to lack of suitable measurement devices and lack of rigorously validated protein panels.Here we report an ultrasensitive electrochemical microfluidic array optimized to measure a four-protein panel of biomarker proteins, and we validate the protein panel for accurate oral cancer diagnostics. Unprecedented ultralow detection into the 5−50 fg•mL −1 range was achieved for simultaneous measurement of proteins interleukin 6 (IL-6), IL-8, vascular endothelial growth factor (VEGF), and VEGF-C in diluted serum. The immunoarray achieves high sensitivity in 50 min assays by using off-line protein capture by magnetic beads carrying 400 000 enzyme labels and ∼100 000 antibodies. After capture of the proteins and washing to inhibit nonspecific binding, the beads are magnetically separated and injected into the array for selective capture by antibodies on eight nanostructured sensors. Good correlations with enzyme-linked immunosorbent assays (ELISA) for protein determinations in conditioned cancer cell media confirmed the accuracy of this approach. Normalized means of the four protein levels in 78 oral cancer patient serum samples and 49 controls gave clinical sensitivity of 89% and specificity of 98% for oral cancer detection, demonstrating high diagnostic utility. The low-cost, easily fabricated immunoarray provides a rapid serum test for diagnosis and personalized therapy of oral cancer. The device is readily adaptable to clinical diagnostics of other cancers.