Showing papers on "Selection (genetic algorithm) published in 2000"

Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools

Abstract: We develop estimation methods that use the amount of selection on the observables in a model as a guide to the amount of selection on the unobservables. We show that if the observed variables are a random subset of a large number of factors that influence the endogenous variable and the outcome of interest, then the relationship between the index of observables that determines the endogenous variable and the index that determines the outcome will be the same as the relationship between the indices of unobservables that determine the two variables. In some circumstances this fact may be used to identify the effect of the endogenous variable. We also propose an informal way to assess selectivity bias based on measuring the ratio of selection on unobservables to selection on observables that would be required if one is to attribute the entire effect of the endogenous variable to selection bias. We use our methods to estimate the effect of attending a Catholic high school on a variety of outcomes. Our main conclusion is that Catholic high schools substantially increase the probability of graduating from high school and, more tentatively, college attendance. We do not find much evidence for an effect on test scores.

The evolution of body size: what keeps organisms small?

Abstract: It is widely agreed that fecundity selection and sexual selection are the major evolutionary forces that select for larger body size in most organisms. The general, equilibrium view is that selection for large body size is eventually counterbalanced by opposing selective forces. While the evidence for selection favoring larger body size is overwhelming, counterbalancing selection favoring small body size is often masked by the good condition of the larger organism and is therefore less obvious. The suggested costs of large size are: (1) viability costs in juveniles due to long development and/or fast growth; (2) viability costs in adults and juveniles due to predation, parasitism, or starvation because of reduced agility, increased detectability, higher energy requirements, heat stress, and/or intrinsic costs of reproduction; (3) decreased mating success of large males due to reduced agility and/or high energy requirements; and (4) decreased reproductive success of large females and males due to late reproduction. A review of the literature indicates a substantial lack of empirical evidence for these various mechanisms and highlights the need for experimental studies that specifically address the fitness costs of being large at the ecological, physiological, and genetic levels. Specifically, theoretical investigations and comprehensive case studies of particular model species are needed to elucidate whether sporadic selection in time and space is sufficient to counterbalance perpetual and strong selection for large body size.

Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework

Abstract: This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be ``embedded'' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem.

The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation

Abstract: We introduce a new multiobjective evolutionary algorithm called PESA (the Pareto Envelope-based Selection Algorithm), in which selection and diversity maintenance are controlled via a simple hyper-grid based scheme. PESA's selection method is relatively unusual in comparison with current well known multiobjective evolutionary algorithms, which tend to use counts based on the degree to which solutions dominate others in the population. The diversity maintenance method is similar to that used by certain other methods. The main attraction of PESA is the integration of selection and diversity maintenance, whereby essentially the same technique is used for both tasks. The resulting algorithm is simple to describe, with full pseudocode provided here and real code available from the authors. We compare PESA with two recent strong-performing MOEAs on some multiobjective test problems recently proposed by Deb. We find that PESA emerges as the best method overall on these problems.

The degeneration of Y chromosomes

Abstract: Y chromosomes are genetically degenerate, having lost most of the active genes that were present in their ancestors. The causes of this degeneration have attracted much attention from evolutionary theorists. Four major theories are reviewed here: Muller's ratchet, background selection, the Hill–Robertson effect with weak selection, and the ‘hitchhiking’ of deleterious alleles by favourable mutations. All of these involve a reduction in effective population size as a result of selective events occurring in a non–recombining genome, and the consequent weakening of the efficacy of selection. We review the consequences of these processes for patterns of molecular evolution and variation at loci on Y chromosomes, and discuss the results of empirical studies of these patterns for some evolving Y–chromosome and neo–Y–chromosome systems. These results suggest that the effective population sizes of evolving Y or neo–Y chromosomes are severely reduced, as expected if some or all of the hypothesized processes leading to degeneration are operative. It is, however, currently unclear which of the various processes is most important; some directions for future work to help to resolve this question are discussed.

The Mathematical Theory of Selection, Recombination, and Mutation

Abstract: Population genetics is concerned with the study of the genetic, ecological, and evolutionary factors that influence and change the genetic composition of populations. The emphasis here is on models that have a direct bearing on evolutionary quantitative genetics. Applications concerning the maintenance of genetic variation in quantitative traits and their dynamics under selection are treated in detail.

Application of genetic algorithm–PLS for feature selection in spectral data sets

Abstract: After suitable modifications, genetic algorithms can be a useful tool in the problem of wavelength selection in the case of a multivariate calibration performed by PLS. Unlike what happens with the majority of feature selection methods applied to spectral data, the variables selected by the algorithm often correspond to well-defined and characteristic spectral regions instead of being single variables scattered throughout the spectrum. This leads to a model having a better predictive ability than the full-spectrum model; furthermore, the analysis of the selected regions can be a valuable help in understanding which are the relevant parts of the spectra. After the presentation of the algorithm, several real cases are shown. Copyright © 2000 John Wiley & Sons, Ltd.

Portfolio Selection and Asset Pricing Models

Abstract: Finance theory can be used to form informative prior beliefs in financial decision making. This paper approaches portfolio selection in a Bayesian framework that incorporates a prior degree of belief in an asset pricing model. Sample evidence on home bias and value and size effects is evaluated from an asset-allocation perspective. U.S. investors' belief in the domestic CAPM must be very strong to justify the home bias observed in their equity holdings. The same strong prior belief results in large and stable optimal positions in the Fama–French book-to-market portfolio in combination with the market since the 1940s.

Density cycles and an offspring quantity and quality game driven by natural selection

Abstract: A long-standing hypothesis posits that natural selection can favour two female strategies when density cycles. At low density, females producing many smaller progeny are favoured when the intrinsic rate of increase, r, governs population growth. At peak density, females producing fewer, high-quality, progeny are favoured when the carrying capacity, K, is exceeded and the population crashes. Here we report on the first example of a genetic r versus K selection game that promotes stable population cycles in lizards. Decade-long fitness studies and game theory demonstrated that two throat-colour morphs were refined by selection in which the strength of natural selection varied with density. Orange-throated females, r strategists, produced many eggs and were favoured at low density. Conversely, yellow-throated females, K strategists, produced large eggs and were favoured at high density. Progeny size should also be under negative frequency-dependent selection in that large progeny will have a survival advantage when rare, but the advantage disappears when they become common. We confirmed this prediction by seeding field plots with rare and common giant hatchlings. Thus, intrinsic causes of frequency- and density-dependent selection promotes an evolutionary game with two-generation oscillations.

The Variable Selection Problem

Abstract: The problem of variable selection is one of the most pervasive model selection problems in statistical applications. Often referred to as the problem of subset selection, it arises when one wants to model the relationship between a variable of interest and a subset of potential explanatory variables or predictors, but there is uncertainty about which subset to use. This vignette reviews some of the key developments that have led to the wide variety of approaches for this problem.

Perspective: sex, recombination, and the efficacy of selection—was weismann right?

Abstract: The idea that sex functions to provide variation for natural selection to act upon was first advocated by August Weismann and it has dominated much discussion on the evolution of sex and recombination since then. The goal of this paper is to further extend this hypothesis and to assess its place in a larger body of theory on the evolution of sex and recombination. A simple generic model is developed to show how fitness variation and covariation interact with selection for recombination and illustrate some important implications of the hypothesis: (1) the advantage of sex and recombination can accrue both to reproductively isolated populations and to modifiers segregating within populations, but the former will be much larger than the latter; (2) forces of degradation that are correlated across loci within an individual can reduce or reverse selection for increased recombination; and (3) crossing-over (which can occur at different places in different meioses) will create more variability than havi...

Project portfolio selection through decision support

Abstract: Project portfolio selection is a crucial decision in many organizations, which must make informed decisions on investment, where the appropriate distribution of investment is complex, due to varying levels of risk, resource requirements, and interaction among the proposed projects. In this paper, we discuss the implementation of an organized framework for project portfolio selection through a decision support system (DSS), which we call Project Analysis and Selection System (PASS). We describe the results of laboratory tests undertaken to measure its usability and quality, compared to manual selection processes, in typical portfolio selection problems. We also discuss the potential of PASS in supporting corporate decision making, through exposure this system has received through demonstrations for several companies.

Personnel selection: looking toward the future--remembering the past

Abstract: This chapter reviews personnel selection research from 1995 through 1999. Areas covered are job analysis; performance criteria; cognitive ability and personality predictors; interview, assessment center, and biodata assessment methods; measurement issues; meta-analysis and validity generalization; evaluation of selection systems in terms of differential prediction, adverse impact, utility, and applicant reactions; emerging topics on team selection and cross-cultural issues; and finally professional, legal, and ethical standards. Three major themes are revealed: (a) Better taxonomies produce better selection decisions; (b) The nature and analyses of work behavior are changing, influencing personnel selection practices; (c) The field of personality research is healthy, as new measurement methods, personality constructs, and compound constructs of well-known traits are being researched and applied to personnel selection.

Methods to Detect Selection in Populations with Applications to the Human

Abstract: ▪ Abstract The development of statistical tests of natural selection at the DNA level in population samples has been ongoing for the past 13 years. The current state of the field is reviewed, and the available tests of selection are described. All tests use predictions from the theory of neutrally evolving sites as a null hypothesis. Departures from equilibrium-neutral expectations can indicate the presence of natural selection acting either at one or more of the sites under investigation or at a sufficiently tightly linked site. Complications can arise in the interpretation of departures from neutrality if populations are not at equilibrium for mutation and genetic drift or if populations are subdivided, both of which are likely scenarios for humans. Attempts to understand the nonequilibrium configuration of silent polymorphism in human mitochondrial DNA illustrate the difficulty of distinguishing between selection and alternative demographic hypotheses. The range of plausible alternatives to selection w...

Marker-assisted selection using ridge regression.

Abstract: In cross between inbred lines, linear regression can be used to estimate the correlation of markers with a trait of interest; these marker effects then allow marker assisted selection (MAS) for quantitative traits. Usually a subset of markers to include in the model must be selected: no completely satisfactory method of doing this exists. We show that replacing this selection of markers by ridge regression can improve the mean response to selection and reduce the variability of selection response.

Feature selection in unsupervised learning via evolutionary search

Abstract: Feature subset selection is an important problem in knowledge discovery, not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalabilit y, and possibly , accuracy of the resulting models. In this paper w e consider the problem of feature selection for unsupervised learning. A number of heuristic criteria can be used to estimate the quality of clusters built from a giv en featuresubset. Rather than combining such criteria, we use ELSA, an evolutionary local selection algorithm that maintains a diverse population of solutions that approximate the Pareto front in a multidimensional objectiv espace. Eac hevolved solution represents a feature subset and a number of clusters; a standard K-means algorithm is applied to form the given n umber of clusters based on the selected features. Preliminary results on both real and synthetic data show promise in nding P areto-optimal solutions through which we can identify the signi cant features and the correct number of clusters.

Artificial ecosystem selection.

Abstract: Artificial selection has been practiced for centuries to shape the properties of individual organisms, providing Darwin with a powerful argument for his theory of natural selection. We show that the properties of whole ecosystems can also be shaped by artificial selection procedures. Ecosystems initiated in the laboratory vary phenotypically and a proportion of the variation is heritable, despite the fact that the ecosystems initially are composed of thousands of species and millions of individuals. Artificial ecosystem selection can be used for practical purposes, illustrates an important role for complex interactions in evolution, and challenges a widespread belief that selection is most effective at lower levels of the biological hierarchy.

Laboratory selection experiments using Drosophila: what do they really tell us?

Abstract: Laboratory selection experiments using Drosophila, and other organisms, are widely used in experimental biology. In particular, such experiments on D. melanogaster life history and stress-related traits have been instrumental in developing the emerging field of experimental evolution. However, similar selection experiments often produce inconsistent correlated responses to selection. Unfortunately, selection experiments are vulnerable to artifacts that are difficult to control. In spite of these problems, selection experiments are a valuable research tool and can contribute to our understanding of evolution in natural populations.

How Does NAEP Select Schools and Students

Abstract: DOCUMENT RESUME

Maximum Likelihood Estimation on Large Phylogenies and Analysis of Adaptive Evolution in Human Influenza Virus A

Abstract: Algorithmic details to obtain maximum likelihood estimates of parameters on a large phylogeny are discussed. On a large tree, an efficient approach is to optimize branch lengths one at a time while updating parameters in the substitution model simultaneously. Codon substitution models that allow for variable nonsynonymous/synonymous rate ratios (omega = d(N)/d(S)) among sites are used to analyze a data set of human influenza virus type A hemagglutinin (HA) genes. The data set has 349 sequences. Methods for obtaining approximate estimates of branch lengths for codon models are explored, and the estimates are used to test for positive selection and to identify sites under selection. Compared with results obtained from the exact method estimating all parameters by maximum likelihood, the approximate methods produced reliable results. The analysis identified a number of sites in the viral gene under diversifying Darwinian selection and demonstrated the importance of including many sequences in the data in detecting positive selection at individual sites.

A quality assurance‐oriented methodology for handling trade‐offs in supplier selection

Abstract: In an era of global sourcing, the firm’s success often hinges on the most appropriate selection of its suppliers. Supplier selection is sometimes very complicated, owing to a variety of uncontrollable and unpredictable factors which affect the decision. Describes a multiple attribute utility theory based on the use of data envelopment analysis (DEA), aimed at helping purchasing managers to formulate viable sourcing strategies in the changing market place. An application of the methodology using actual data retrieved from a firm operating in the bottling industry is illustrated. DEA has proved to be capable of handling multiple conflicting attributes inherent in supplier selection while simultaneously trading‐off key supplier selection criteria.

Method and system for providing alternatives for text derived from stochastic input sources

Abstract: A computer-implemented method for providing a candidate list of alternatives for a text selection containing text from multiple input sources, each of which can be stochastic (such as a speech recognition unit, handwriting recognition unit, or input method editor) or non-stochastic (such as a keyboard and mouse). A text component of the text selection may be the result of data processed through a series of stochastic input sources, such as speech input that is converted to text by a speech recognition unit before being used as input into an input method editor. To determine alternatives for the text selection, a stochastic input combiner parses the text selection into text components from different input sources. For each stochastic text component, the combiner retrieves a stochastic model containing alternatives for the text component. If the stochastic text component is the result of a series of stochastic input sources, the combiner derives a stochastic model that accurately reflects the probabilities of the results of the entire series. The combiner creates a list of alternatives for the text selection by combining the stochastic models retrieved. The combiner may revise the list of alternatives by applying natural language principles to the text selection as a whole. The list of alternatives for the text selection is then presented to the user. If the user chooses one of the alternatives, then the word processor replaces the text selection with the chosen candidate.