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Broken Biological Size Relationships: A Truncated Semiparametric Regression Approach with Measurement Error

生物尺寸关系的断裂:含测量误差的截断半参数回归

Biological size relationships (i.e., regression of one size variable on another) are typically monotone but often break down at extreme values of the variables. Here we study the way in which a plant's biomass is apportioned to reproductive and other life activities. Working with a theory proposed by Weiner (1988) based an analogy between a biological plant and an industrial plant leads to a truncated regression model formulation. We consider a dataset involving 542…

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Optimal Unbiased Tests for Equivalence in Intrasubject Variability

个体内变异等效性的最优无偏检验

The equivalence in average bioavailability between formulations may not be sufficient for assessment of bioequivalence. The difference in intrasubject variability between formulations should also be considered. This article presents an unbiased test procedure for equivalence in intrasubject variability of bioavailability that is uniformly more powerful than the two one-sided tests procedure proposed by Liu and Chow. Under a stronger condition, a uniformly most powerful…

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Data-Driven Smooth Tests When the Hypothesis is Composite

复合假设下的数据驱动光滑检验

In recent years several authors have recommended smooth tests for testing goodness of fit. However, the number of components in the smooth test statistic should be chosen well; otherwise, considerable loss of power may occur. Schwarz's selection rule provides one such good choice. Earlier results on simple null hypotheses are extended here to composite hypotheses, which tend to be of more practical interest. For general composite hypotheses, consistency of the data-driven…

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Empirical-Bias Bandwidths for Local Polynomial Nonparametric Regression and Density Estimation

局部多项式回归与密度估计的经验偏差带宽

A data-based local bandwidth selector is proposed for nonparametric regression by local fitting of polynomials. The estimator, called the empirical-bias bandwidth selector (EBBS), is rather simple and easily allows multivariate predictor variables and estimation of any order derivative of the regression function. EBBS minimizes an estimate of mean squared error consisting of a squared bias term plus a variance term. The variance term used is exact, not asymptotic, though it…

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Robust Linear Model Selection by Cross-Validation

通过交叉验证进行稳健线性模型选择

This article gives a robust technique for model selection in regression models, an important aspect of any data analysis involving regression. There is a danger that outliers will have an undue influence on the model chosen and distort any subsequent analysis. We provide a robust algorithm for model selection using Shao's cross-validation methods for choice of variables as a starting point. Because Shao's techniques are based on least squares, they are sensitive to outliers.…

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Testing the Independence Assumption in Linear Models

检验线性模型中的独立性假设

We propose using an existing set of statistical tools in a new way that allows one to test the independence assumption in standard normal theory linear models. The set of tools is near-replicate lack-of-fit tests. The classical lack-of-fit test requires a linear model in which some rows of the model matrix are repeated. Near-replicate lack-of-fit tests were developed to mimic the behavior of the classical test by identifying clusters of rows in the design matrix that are…

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Influence Diagnostics for Linear Longitudinal Models

线性纵向模型的影响诊断

Influence diagnostics are important for analyzing cross-sectional regression studies, because they allow the analyst to understand the impact of individual observations on the estimated regression model. In this article we consider the role of influence diagnostics in subject-specific longitudinal models. Diagnostics are proposed under both fixed and random subject effects. Our approach is based on subject deletion, which in this setting involves deleting a group of…

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Nonparametric Maximum Likelihood Estimation from Samples with Irrelevant Data and Verification Bias

含无关数据与核验偏差样本的非参数极大似然估计

Suppose that some measurements come from a distribution F that is of interest and others come from another, irrelevant distribution G. Some measurements from F are verified and known to be from F. The other, unverified measurements may be from F or from G. Not all measurements from F are equally likely to be verified, and no measurement from G is ever verified. This model applies to measurements of low concentrations obtained using gas chromatography/mass spectroscopy, for…

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Computing Bayes Factors by Combining Simulation and Asymptotic Approximations

结合模拟与渐近近似计算贝叶斯因子

The Bayes factor is a ratio of two posterior normalizing constants, which may be difficult to compute. We compare several methods of estimating Bayes factors when it is possible to simulate observations from the posterior distributions, via Markov chain Monte Carlo or other techniques. The methods that we study are all easily applied without consideration of special features of the problem, provided that each posterior distribution is well behaved in the sense of having a…

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Analyses of Fish Species Richness with Spatial Covariate

包含空间协变量的鱼类物种丰富度分析

Legislation passed in 1990 reducing the allowable sulfur dioxide emission levels in the United States is expected to reduce acidity in the Adirondack region of New York State. The number of fish species in a lake (species richness) depends on a number of physical and chemical factors, including the area, elevation, and acidity of the lake. Data on these and other factors are available for 1,166 Adirondack lakes. The data are analyzed with the goal of quantifying the effects…

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Small Area Inference for Binary Variables in the National Health Interview Survey

全国健康访谈调查中二元变量的小区域推断

The National Health Interview Survey is designed to produce precise estimates of finite population parameters for the entire United States but not for small geographical areas or subpopulations. Our investigation concerns estimates of proportions such as the probability of at least one visit to a doctor within the past 12 months. To include all sources of variation in the model, we carry out a Bayesian hierarchical analysis for the desired finite population quantities.…

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Statistical Methods for Profiling Providers of Medical Care: Issues and Applications

医疗服务提供者绩效画像的统计方法与应用

Recent public debate on costs and effectiveness of health care in the United States has generated a growing emphasis on “profiling” of medical care providers. The process of profiling involves comparing resource use and quality of care among medical providers to a community or a normative standard. This is valuable for targeting quality improvement strategies. For example, hospital profiles may be used to determine whether institutions deviate in important ways in the…

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Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques.

物理应用中的谱分析:多窗与传统单变量技术

Glossary of symbols 1. Introduction to spectral analysis 2. Stationary stochastic processes 3. Deterministic spectral analysis 4. Foundations for stochastic spectral theory 5. Linear time-invariant filters 6. Non-parametric spectral estimation 7. Multiple taper spectral estimation 8. Calculation of discrete prolate spheroidal sequences 9. Parametric spectral estimation 10. Harmonic analysis References Appendix: data and code via e-mail Index.

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Statistical Tools for Nonlinear Regression: A Practical Guide with S-PLUS Examples.

非线性回归的统计工具:含 S-PLUS 示例的实用指南

Presenting methods for analysing data using parametric nonlinear regression models, this text uses examples from experiments in agronomy and biochemistry, and shows how to apply the methods. The book includes methods based on classical nonlinear regression theory, as well as more modern ones such as the bootstrap. The examples are analysed with the software program nls2 implemented in S-PLUS. Examples in biology and agriculture are emphasized.

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An Approximate Likelihood Ratio Test for Comparing Several Treatments to a Control

比较多个处理与对照的近似似然比检验

Some parametric tests for comparing several treatments to a control are examined. Those tests developed earlier tend to rest on a single principle: Simplicity or power; those developed later attempt to fill the gap. We propose a new test that represents another such attempt. The basic idea is to find a simple statistic that is a good approximation to the likelihood ratio statistic. This leads to a power function similar to that of the likelihood ratio test, which is optimal…

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An Efficient Estimator for the Generalized Semilinear Model

广义半线性模型的有效估计量

The generalized semilinear model (GSLIM) extends the generalized linear model by allowing the addition of an unknown smooth function to the predictor parameter, producing a semiparametric model. Some previously proposed score-based estimators for the parametric component in this model are not √n consistent. We propose efficient estimators for both the parametric and nonparametric components of the GSLIM. The estimator for the parametric component is the solution to an…

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Testing the Independence Assumption in Linear Models

线性模型中独立性假设的检验

We propose using an existing set of statistical tools in a new way that allows one to test the independence assumption in standard normal theory linear models. The set of tools is near-replicate lack-of-fit tests. The classical lack-of-fit test requires a linear model in which some rows of the model matrix are repeated. Near-replicate lack-of-fit tests were developed to mimic the behavior of the classical test by identifying clusters of rows in the design matrix that are…

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Modeling Long-Range Dependence, Nonlinearity, and Periodic Phenomena in Sea Surface Temperatures Using TSMARS

用 TSMARS 建模海表温度的长程依赖、非线性与周期现象

We analyze a time series of 20 years of daily sea surface temperatures measured off the California coast. The temperatures exhibit quite complicated features, such as effects on many different time scales, nonlinear effects, and long-range dependence. We show how a time series version of the multivariate adaptive regression splines (MARS) algorithm, TSMARS, can be used to obtain univariate adaptive spline threshold autoregressive models that capture many of the physical…

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Broken Biological Size Relationships: A Truncated Semiparametric Regression Approach With Measurement Error

生物体大小关系的失效:含测量误差的截断半参数回归

Biological size relationships (i.e., regression of one size variable on another) are typically monotone but often break down at extreme values of the variables. Here we study the way in which a plant's biomass is apportioned to reproductive and other life activities. Working with a theory proposed by Weiner (1988) based an analogy between a biological plant and an industrial plant leads to a truncated regression model formulation. We consider a dataset involving 542…

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