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通过随机外显率确定遗传分布AI 解读

The aim of linkage analysis is to map the position of a gene contributing to an inheritable disease. The statistical model contains the disease allele frequency and penetrance parameters. Here I investigate the inheritance distribution, that is, the conditional distribution of the inheritance vector given phenotypes at the disease locus. Based on this, the likelihood and likelihood score function of Whittemore can be defined. As a result, a general semiparametric methodology…

完全标记信息下多点连锁分析的渐近估计理论AI 解读

We consider estimation of a disease susceptibility locus $\tau$ at a chromosome. With perfect marker data available, the estimator $\htau_N$ of $\tau$ based on $N$-pedigrees has a rate of convergence $N^{-1}$ under mild regularity conditions. The limiting distribution is the arg max of a certain compound Poisson process. Our approach is conditional on observed phenotypes, and therefore treats parametric and nonparametric linkage, as well as quantitative trait loci methods…

最小修剪差分回归估计量及其替代方法AI 解读

This article proposes and studies the performance in theory and practice of the least trimmed differences (LTD) linear regression estimator. The estimator minimizes the sum of the smallest quartile of the squares of the differences in each pair of residuals. We obtain the breakdown point, maxbias curve, and large-sample properties of a class of estimators including the LTD as special case. The LTD estimator has a 50% breakdown point and Gaussian efficiency of…

不完全广义 L 统计量AI 解读

Given data $X_1, \dots, X_n$ and a kernel h with m arguments, Serfling introduced the class of generalized L-statistics (GL-statistics), which is defined by taking linear combinations of the ordered $h(X_{i_1}, \dots, X_{i_m})$ where $(i_1, \dots, i_m)$ ranges over all $n!/(n - m)!$ distinct m-tuples of $(1, \dots, n)$. In this paper we derive a class of incomplete generalized L-statistics (IGL-statistics) by taking linear combinations of the ordered elements from a subset…

广义 S 估计量AI 解读

In this article we introduce a new type of positive-breakdown regression method, called a generalized S-estimator (or GS-estimator), based on the minimization of a generalized M-estimator of residual scale. We compare the class of GS-estimators with the usual S-estimators, including least median of squares. It turns out that GS-estimators attain a much higher efficiency than S-estimators, at the cost of a slightly increased worst-case bias. We investigate the breakdown…

线性模型中具有高崩溃点的秩估计AI 解读

An estimator in the linear model is defined by minimizing an objective function, the derivative of which is a signed rank statistic. The scores are generated from a function h+ : (0, 1) → [0, ∞), which is not necessarily nondecreasing, as is usually assumed. It is shown that this estimator can be chosen with a maximal breakdown point of. 5. Moreover, strong consistency and asymptotic normality (with convergence rate n −1/2 of the proposed estimator are proved under various…