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Showing 1 to 5 of 5 for “"selection statistics"”.

  1. Human population history and its interplay with natural selection

    … consequences on the dynamics of natural selection and our ability to detect it. In this thesis, I aimed to refine our knowledge on human population history using ancient genomes, and then used a climate-informed, spatially explicit framework to explore the interplay between complex …

    cambridge Repository record for Human population history and its interplay with natural selection (opens in a new tab)

  2. An economic analysis of the impact of alternative government peanut programs on program costs and the farm production sector of the Virginia-North Carolina peanut industry

    … 700 million pounds. Results also show that the selection of a peanut program could reduce labor requirements of area farms by 6 percent or increase the needed labor force by 4 percent. They further indicate that program selection could cause a variation in gross receipts of $22 million and a …

    vt Repository record for An economic analysis of the impact of alternative government peanut programs on program costs and the farm production sector of the Virginia-North Carolina peanut industry (opens in a new tab)

  3. One and Two-Step Estimation of Time Variant Parameters and Nonparametric Quantiles

    <p>This dissertation develops and discusses several one-step and two-step smoothing methods of time variant nonparametric quantiles and time variant parameters from probability models. First, we investigate and develop nonparametric techniques for measuring extreme quantiles. The method involves …

    kennesaw Repository record for One and Two-Step Estimation of Time Variant Parameters and Nonparametric Quantiles (opens in a new tab)

  4. Model-Free Variable Screening, Sparse Regression Analysis and Other Applications with Optimal Transformations

    <p>Variable screening and variable selection methods play important roles in modeling high dimensional data. Variable screening is the process of filtering out irrelevant variables, with the aim to reduce the dimensionality from ultrahigh to high while retaining all important variables. Variable …

    purdue-thes Repository record for Model-Free Variable Screening, Sparse Regression Analysis and Other Applications with Optimal Transformations (opens in a new tab)