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Multiple regression approach to mapping of quantitative trait loci (QTL) based on sib-pair data: a theoretical analysis

基于同胞配对数据定位数量性状位点的多元回归理论分析

The interval mapping method has been shown to be a powerful tool for mapping QTL. However, it is still a challenge to perform a simultaneous analysis of several linked QTLs, and to isolate multiple linked QTLs. To circumvent these problems, multiple regression analysis has been suggested for experimental species. In this paper, the multiple regression approach is extended to human sib-pair data through multiple regression of the squared difference in trait values between two…

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Asymptotics for lasso-type estimators

Lasso 型估计量的渐近性质

We consider the asymptotic behavior ofregression estimators that minimize the residual sum of squares plus a penalty proportional to $\sum|\beta_j|^{\gamma}$. for some $\gamma > 0$. These estimators include the Lasso as a special case when $\gamma = 1$. Under appropriate conditions, we show that the limiting distributions can have positive probability mass at 0 when the true value of the parameter is 0.We also consider asymptotics for “nearly singular” designs.

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Inference in Long‐Horizon Event Studies: A Bayesian Approach with Application to Initial Public Offerings

长期事件研究中的推断:贝叶斯方法及首次公开发行应用

Statistical inference in long‐horizon event studies has been hampered by the fact that abnormal returns are neither normally distributed nor independent. This study presents a new approach to inference that overcomes these difficulties and dominates other popular testing methods. I illustrate the use of the methodology by examining the long‐horizon returns of initial public offerings (IPOs). I find that the Fama and French (1993) three‐factor model is inconsistent with the…

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Forecasting the Penetration of a New Product: A Bayesian Approach

新产品市场渗透预测:贝叶斯方法

We adopt a Bayesian approach to forecast the penetration of a new product into a market. We incorporate prior information from an existing product and/or management judgments into the data analysis. The penetration curve is assumed to be a nondecreasing function of time and may be under shape constraints. Markov-chain Monte Carlo methods are proposed and used to compute the Bayesian forecasts. An example on forecasting the penetration of color television using the…

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Forecasting the Penetration of a New Product—A Bayesian Approach

新产品市场渗透率预测:贝叶斯方法

We adopt a Bayesian approach to forecast the penetration of a new product into a market. We incorporate prior information from an existing product and/or management judgments into the data analysis. The penetration curve is assumed to be a nondecreasing function of time and may be under shape constraints. Markov-chain Monte Carlo methods are proposed and used to compute the Bayesian forecasts. An example on forecasting the penetration of color television using the…

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Long Memory in Stock-Market Trading Volume

股市交易量的长记忆性

This article examines consistent estimation of the long-memory parameters of stock-market trading volume and volatility. The analysis is carried out in the frequency domain by tapering the data instead of detrending them. The main theoretical contribution of the article is to prove a central limit theorem for a multivariate two-step estimator of the memory parameters of a nonstationary vector process. Using robust semiparametric procedures, the long-memory properties of…

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Inequality Orderings, Normalized Stochastic Dominance, and Statistical Inference

不平等排序、归一化随机占优与统计推断

This article derives large-sample properties and provides asymptotically distribution-free statistical inference procedures for an alternative approach to inequality orderings—normalized stochastic dominance (NSD). NSD is a straightforward extension of standard dominance techniques. As such, it can be generalized to higher orders of dominance, thereby providing a more powerful technique for ranking distributions. We illustrate the NSD method by applying it to Current…

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Testing for the Cointegrating Rank of a VAR Process With Structural Shifts

含结构突变的VAR过程的协整秩检验

Tests for the cointegrating rank of a vector autoregressive process are considered that allow for possible exogenous shifts in the mean of the data-generation process. The break points are assumed to be known a priori. It is proposed to estimate and remove the deterministic terms such as mean, linear-trend term, and a shift in a first step. Then systems cointegration tests are applied to the adjusted series. The resulting tests are shown to have known limiting null…

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LOCAL SEMIPARAMETRIC EFFICIENCY BOUNDS UNDER SHAPE RESTRICTIONS

形状约束下的局部半参数效率界

Consider the model y = x ′ β 0 + f * ( z ) + ε, where ε [d over =] N(0, σ 0 2 ). We calculate the smallest asymptotic variance that n 1/2 consistent regular ( n 1/2 CR) estimators of β 0 can have when the only information we possess about f * is that it has a certain shape. We focus on three particular cases: (i) when f * is homogeneous of degree r , (ii) when f * is concave, (iii) when f * is decreasing. Our results show that in the class of all n 1/2 CR estimators of β 0 ,…

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A BARTLETT CORRECTION FACTOR FOR TESTS ON THE COINTEGRATING RELATIONS

协整关系检验的 Bartlett 修正因子

Likelihood ratio tests for restrictions on cointegrating vectors are asymptotically χ 2 distributed. For some values of the parameters this asymptotic distribution does not give a good approximation to the finite sample distribution. In this paper we derive the Bartlett correction factor for the likelihood ratio test and show by some simulation experiments that it can be a useful tool for making inference.

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ESTIMATING WEAK GARCH REPRESENTATIONS

弱 GARCH 表示的估计

The classical definitions of GARCH-type processes rely on strong assumptions on the first two conditional moments. The common practice in empirical studies, however, has been to test for GARCH by detecting serial correlations in the squared regression errors. This can be problematic because such autocorrelation structures are compatible with severe misspecifications of the standard GARCH. Numerous examples are provided in the paper. In consequence, standard (quasi-) maximum…

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A CONSISTENT TEST OF CONDITIONAL PARAMETRIC DISTRIBUTIONS

条件参数分布的一致性检验

This paper proposes a new nonparametric test for conditional parametric distribution functions based on the first-order linear expansion of the Kullback–Leibler information function and the kernel estimation of the underlying distributions. The test statistic is shown to be asymptotically distributed standard normal under the null hypothesis that the parametric distribution is correctly specified, whereas asymptotically rejecting the null with probability one if the…

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BEHAVIOR OF DICKEY–FULLER t -TESTS WHEN THERE IS A BREAK UNDER THE ALTERNATIVE HYPOTHESIS

备择假设下存在断点时 Dickey–Fuller t 检验的行为

This paper analyzes the limiting behavior of Dickey–Fuller t -tests when the true generating model is stationary around a broken linear trend. The cases of a break in level and a break in slope are considered separately and found to generate qualitatively different outcomes. In the asymptotic analysis, appropriate normalizations are applied to the break sizes. This leads to theoretical results that generate interesting predictions for sample sizes and break amounts of…

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THE FUNCTIONAL CENTRAL LIMIT THEOREM AND WEAK CONVERGENCE TO STOCHASTIC INTEGRALS I

函数型中心极限定理与随机积分的弱收敛(一)

This paper gives new conditions for the functional central limit theorem, and weak convergence of stochastic integrals, for near-epoch-dependent functions of mixing processes. These results have fundamental applications in the theory of unit root testing and cointegrating regressions. The conditions given improve on existing results in the literature in terms of the amount of dependence and heterogeneity permitted, and in particular, these appear to be the first such…

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Miscellanea. A robust imputation method for surrogate outcome data

杂论:替代结局数据的稳健插补方法

We consider estimation for regression analysis with surrogate or auxiliary outcome data. Assume that the regression model for the conditional mean of the outcome is a known function of a linear combination of the covariates with unknown coefficients, which are the regression parameters of interest. Such a class of models includes the generalised linear models as special cases. Suppose further that the outcome variable of interest is only observed in a validation subset,…

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Breakdown points of t-type regression estimators

t 型回归估计量的崩溃点

To bound the influence of a leverage point, generalised M-estimators have been suggested. However, the usual generalised M-estimator of regression has a breakdown point that is less than the inverse of its dimension. This paper shows that dimension-independent positive breakdown points can be attained by a class of well-defined generalised M-estimators with redescending scores. The solution can be determined through optimisation of t-type likelihood applied to properly…

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Tests for monotonicity of a regression mean with guaranteed level

具有显著性水平保证的回归均值单调性检验

In this paper a nonparametric procedure for testing for monotonicity of a regression mean with guaranteed level is proposed. The procedure is based on signs of differences of observations from the response variable. The test is calibrated against the most difficult null hypothesis, when the regression function is constant, and produces an exact test in this context. In general, the test is conservative. The power of the test is good, and comparable with that of other…

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A nonparametric approach to the analysis of two-stage mark-recapture experiments

两阶段标记重捕实验分析的非参数方法

We present a new approach to the analysis of two-stage mark-recapture experiments where individual covariates are available which describe the detectability of individuals in the population. Central to the theory is a single quantity α, which we call the heterogeneity index and which measures the variability in the detectability of individuals. This theory also has implications for the analysis of independent observer line transect surveys. An estimator of α is provided by…

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Principal component analysis based on robust estimators of the covariance or correlation matrix: influence functions and efficiencies

基于稳健协方差或相关矩阵估计的主成分分析:影响函数与效率

A robust principal component analysis can be easily performed by computing the eigenvalues and eigenvectors of a robust estimator of the covariance or correlation matrix. In this paper we derive the influence functions and the corresponding asymptotic variances for these robust estimators of eigenvalues and eigenvectors. The behaviour of several of these estimators is investigated by a simulation study. It turns out that the theoretical results and simulations favour the use…

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Consistency of the bootstrap procedure in individual bioequivalence

Recently, the concepts of population and individual bioequivalence have been proposed for assessing the bioequivalence of two drug formulations. Moment-based and probability-based measures of bioequivalence have led to criteria for deciding whether two formulations should be regarded as bioequivalent or not. The US Food and Drug Administration (1997) guidance recommended the use of bootstrap percentile intervals for this purpose. In this paper, we discuss theoretical…

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On association in a copula with time transformations

带时间变换的 Copula 中的关联性

We consider estimation of the cross ratio in Clayton's (1978) copula in which covariates are incorporated into the marginal distributions via semiparametric accelerated life regression models. Generalisations of Oakes' (1982, 1986) concordance estimating equations yield a closed form for the association parameter under right censoring. Joint inferences about covariate effects in the marginal models and the cross ratio are obtained with U-statistics, martingales and a…

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Nonparametric models and methods for nonlinear analysis of covariance

非线性协方差分析的非参数模型与方法

A fully nonparametric model for nonlinear analysis of covariance is proposed. The term nonlinear means that the covariate influences the response in a possibly nonlinear and nonpolynomial fashion, while the term fully nonparametric implies that the distributions for each factor level combination and covariate value are not restricted to comply with any parametric or semiparametric model. The possibility of different shapes of covariate effect in different factor level…

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On autocorrelation in a Poisson regression model

泊松回归模型中的自相关

This paper develops a practical approach to diagnosing the existence of a latent stochastic process in the mean of a Poisson regression model. The asymptotic distribution of standard generalised linear model estimators is derived for the case where an autocorrelated latent process is present. Simple formulae for the effect of autocovariance on standard errors of the regression coefficients are also provided. Methods for adjusting for the severe bias in previously proposed…

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