Selection (genetic algorithm)

About: Selection (genetic algorithm) is a research topic. Over the lifetime, 72443 publications have been published within this topic receiving 1327417 citations.

ProtTest: selection of best-fit models of protein evolution

Abstract: Summary: Using an appropriate model of amino acid replacement is very important for the study of protein evolution and phylogenetic inference. We have built a tool for the selection of the best-fit model of evolution, among a set of candidate models, for a given protein sequence alignment. Availability: ProtTest is available under the GNU license from http://darwin.uvigo.es Contact: fabascal@uvigo.es

Resource Selection by Animals : Statistical design and analysis for field studies

Abstract: Preface. List of Symbols. 1. Introduction to Resource Selection Studies. 2. Statistical Modelling Procedures. 3. Examples of the Use of Resource Selection Functions. 4. Studies with Resources Defined by Several Categories. 5. Resource Selection Functions from Logistic Regression. 6. Resource Selection over Several Time Periods. 7. Log-Linear Modelling. 8. Discrete Choice Models with Changing Availability. 9. Applications Using Geographic Information Systems. 10. Discriminant Function Analysis. 11. Analysis of the Amount of Use. 12. Some Other Types of Analysis. 13. Risk Assessment and Population Size Estimation. 14. Computing. References. Name Index. Subject Index.

Intra-sexual selection in Drosophila.

Abstract: SINCE Darwin first wrote on the subject in 1871, sexual selection has been generally accepted as one of the basic facts of biology. The evidence in its favour seems, however, to be mainly circumstantial. Its existence has usually been inferred from sex differences depending on what are called secondary sexual characters which are supposed to have arisen as results of that selection. Such an approach has its dangers, and Huxley (1938) has made important criticisms of the original concept of sexual selection. He has shown that a large number of characters which have been attributed to sexual selection are unconnected with competition for mates. This is particularly the case in monogamous birds which offer some of the most striking examples of secondary sexual differences. In the first place monogamy, at least when the sexes are numerically equal, is the mating system least likely to develop sexual selection. In the second place, and more important, observations on bird behaviour have shown that much of the display of birds occurs after pairing, when competition must have ceased. Such sexual differences are concerned, either with inducing the female to copulate, or with maintaining the association of the sexes as long as it is necessary for the rearing of the young. Huxley therefore introduced the term epigamic to apply to characters which increased the fertility of a given mating and therefore had a selective value for the species as a whole. Epigamic selection includes the major part of what Darwin meant by sexual selection. It also includes selection for characters to which Darwin did not refer, such as the structure of copulatory organs, sex differences in frequency of crossing over, and the XY mechanism. It is only a special case of natural selection as generally understood. What remains of Darwinian sexual selection has been called intra-sexual selection, which denotes that it involves competition between members of one sex for mates. It can only indirectly affect the survival of the species and then is often deleterious (e.g. the cumbersome antlers of the stag). There is not invariably, however, a clear distinction between epigamic and intrasexual selection. In a promiscuous species like Drosophila pairing and copulation are synchronous. Courtship behaviour determines the number of mates and therefore enters into intra-sexual selection.

Materials Selection for Mechanical Design

Abstract: The design process engineering materials and their properties materials selection charts materials selection without shape selection of material and shape materials processing and design sources of material property data materials, aesthetics and industrial design forces for change case studies.

Nearly unbiased variable selection under minimax concave penalty

Abstract: We propose MC+, a fast, continuous, nearly unbiased and accurate method of penalized variable selection in high-dimensional linear regression. The LASSO is fast and continuous, but biased. The bias of the LASSO may prevent consistent variable selection. Subset selection is unbiased but computationally costly. The MC+ has two elements: a minimax concave penalty (MCP) and a penalized linear unbiased selection (PLUS) algorithm. The MCP provides the convexity of the penalized loss in sparse regions to the greatest extent given certain thresholds for variable selection and unbiasedness. The PLUS computes multiple exact local minimizers of a possibly nonconvex penalized loss function in a certain main branch of the graph of critical points of the penalized loss. Its output is a continuous piecewise linear path encompassing from the origin for infinite penalty to a least squares solution for zero penalty. We prove that at a universal penalty level, the MC+ has high probability of matching the signs of the unknowns, and thus correct selection, without assuming the strong irrepresentable condition required by the LASSO. This selection consistency applies to the case of $p\gg n$, and is proved to hold for exactly the MC+ solution among possibly many local minimizers. We prove that the MC+ attains certain minimax convergence rates in probability for the estimation of regression coefficients in $\ell_r$ balls. We use the SURE method to derive degrees of freedom and $C_p$-type risk estimates for general penalized LSE, including the LASSO and MC+ estimators, and prove their unbiasedness. Based on the estimated degrees of freedom, we propose an estimator of the noise level for proper choice of the penalty level.