RESUMO
Bimodal data sets are very common in different areas of knowledge. The crude birth rates data, fish length data, egg diameter data, the eruption and interruption times of the Old Faithful geyser, are examples of this type of data. In this paper, a new class of symmetric density functions for modeling bimodal data as described above are presented. From density functions with support on [ 0 , + ∞ ) , the symmetry is getting by reflecting the density function in the negative semi-axis with their respective normalization. In this way, if the primitive density function is unimodal, then the resulting density will be bimodal. We introduce asymmetry parameters and study their behavior, in particular the values of their modes and some other statistical values of interest. The cases for densities generated by Gamma, Weibull, Log-normal, and Birnbaum-Saunders densities, among others are studied. Statistical inference is performed from a classical perspective. A small simulation study to evaluate the benefits and limitations of the new proposal. In addition, an application to a data set related to the fetal weight in grams obtained through ultrasound in a sample of 500 units is also presented; the results show the great usefulness of the model in practical situations.
RESUMO
A forequarter amputation is a radical ablative surgical procedure that includes the entire upper extremity with its shoulder girdle. We present a 53-year-old woman with a solid slow growing tumor in her right shoulder of 15 x 20 cm in diameter. Resection and immediate reconstruction with a free radial forearm flap extended from the distal third of the arm to the midpalmar region, taking the humeral artery and the cephalic vein as a main peddicle. The final outcome is shown at six weeks after the surgery.
RESUMO
The average exclusion probability is a measure of efficiency in paternity testing; it refers to the a priori ability of a battery of tests to detect paternity inconsistencies. This parameter measures the capacity of the system to detect a false accusation of paternity. Traditionally, this average exclusion probability has been estimated as the probability of excluding a man who is not the father by an inconsistency in at least one of the studied loci. We suggest that this criterion should be corrected, as currently the presumed father is excluded when at least three genetic inconsistencies are found with the child being tested, not just one. This change of criterion has occurred because of the use of microsatellite loci, whose mutation rates are much greater than those of the coding genes used previously in paternity studies. We propose the use of the average probability of exclusion for at least three loci (not only one), as an honest measure of the combined probability of exclusion of several loci, and we propose an algebraic expression to calculate it.
