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The Statistical Theory of Shape

形状的统计理论

1 Introduction.- 1.1 Background of Shape Theory.- 1.2 Principles of Allometry.- 1.3 Defining and Comparing Shapes.- 1.4 A Few More Examples.- 1.4.1 A Simple Example in One Dimension.- 1.4.2 Dinosaur Trackways From Mt. Tom, Massachusetts.- 1.4.3 Bronze Age Post Mold Configurations in England.- 1.5 The Problem of Homology.- 1.6 Notes.- 1.7 Problems.- 2 Background Concepts and Definitions.- 2.1 Transformations on Euclidean Space.- 2.1.1 Properties of Sets.- 2.1.2 Affine…

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Multidimensional medians arising from geodesics on graphs

由图上测地线构造的多维中位数

In this paper we introduce a depth function for distributions on graphs that is analogous to recent multivariate definitions. Using the property of geodesic convexity on graphs, a median-like center for distributions on graphs is constructed and applied to ranking data as well as multivariate data spanned by the minimal spanning tree.

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Nonparametric Neyman-Scott problems: Telescoping product methods

非参数 Neyman–Scott 问题:望远镜乘积方法

In this paper, we consider some generalizations of the Neyman-Scott problem of estimating a common variance in the presence of infinitely many mean nuisance parameters. For example, suppose observations are independent and stratified such that they have common distribution of the form F(x-μk) within the kth stratum. If both F and the location parameters μk are unknown, then estimates for F, obtained by centring the samples in each stratum and constructing an estimate…

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A projected likelihood function for semiparametric models

半参数模型的投影似然函数

In a sequence of papers, McLeish (1984), Hutton & Nelson (1986) and Godambe & Heyde (1987) have motivated the use of the quasi-score function as an estimating function for semiparametric models by showing that it is the projection of the true score into a class of unbiased estimating functions. Thus the quasi-score approximates the score within this class of functions. In this paper, we introduce a class of inference functions for independent observations that contain…

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Projection as a Method for Increasing Sensitivity and Eliminating Nuisance Parameters

以投影提高敏感性并消除干扰参数

This paper examines statistical methods based upon estimating functions, i.e. functions of both the parameter and data that are designed to permit inference about an unknown parameter in a statistical model. We explore reductions of such estimating functions by projection. This reduction, analogous to the process of Rao–Blackwellization, may be used either to increase the power of a test, the efficiency of a point estimator, or alternatively to render an inference function…

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Projection as a method for increasing sensitivity and eliminating nuisance parameters

通过投影提高敏感性并消除干扰参数

This paper examines statistical methods based upon estimating functions, i.e. functions of both the parameter and data that are designed to permit inference about an unknown parameter in a statistical model. We explore reductions of such estimating functions by projection. This reduction, analogous to the process of Rao–Blackwellization, may be used either to increase the power of a test, the efficiency of a point estimator, or alternatively to render an inference function…

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Generalizations of Ancillarity, Completeness and Sufficiency in an Inference Function Space

推断函数空间中辅助性、完全性与充分性的推广

In this paper we introduce $E$-ancillarity and complete $E$-sufficiency, natural extensions of the definitions of ancillarity and complete sufficiency to a space of estimating or inference functions. These are functions of both the data and the parameter. We begin either with a space of all such functions or with a subset defined to exploit special features of a model; for example, we allow restrictions to inference functions that are linear in the observations or linear in…

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Likelihood Methods for the Discrimination Problem

判别问题的似然方法

Suppose independent observations are drawn such that k have a known density g(x) and n – k have a known density f(x). We consider the discrimination problem of allocating observations to their parent densities. The rule minimizing the expected number of misclassifications is written as a function of k and estimators of k are investigated. Properties of the likelihood function of k based upon the order statistics are studied. We conclude that a mixture model analysis performs…

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Likelihood methods for the discrimination problem

判别问题的似然方法

Suppose independent observations are drawn such that k have a known density g(x) and n – k have a known density f(x). We consider the discrimination problem of allocating observations to their parent densities. The rule minimizing the expected number of misclassifications is written as a function of k and estimators of k are investigated. Properties of the likelihood function of k based upon the order statistics are studied. We conclude that a mixture model analysis performs…

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Characterization of Type from Maximal Invariant Spectra

由最大不变量谱刻画分布的仿射类型

The affine type of distributions on the real line are represented as sequences of distributions of maximal invariants on spheres. It is shown that such a representation characterizes the affine type. A consistency condition is introduced, and it is shown that any sequence of maximal invariant distributions satisfying the condition is generated by some affine type on $\mathbf{R}$.

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