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日期精度:到日 2268 篇 · 到月 7741 篇 · 到年 0 篇
The Total Least Squares Problem: Computational Aspects and Analysis
Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-PLUS Illustrations
Nonparametric Two-Sample Comparisons of Changes on Ordinal Responses
有序响应变化的非参数两样本比较
We discuss two-armed clinical trials in which an ordinal response is observed on entry and at follow-up. In certain subject areas, such data are often reduced to the counts of patients who have deteriorated, remained the same, or improved. We develop asymptotic distribution theory to compare this approach to the use of nonparametric tests based on poststratification of the follow-up responses according to the entry levels. The theory for the latter approach is established by…
Bayesian Multiscale Models for Poisson Processes
泊松过程的贝叶斯多尺度模型
I introduce a class of Bayesian multiscale models (BMSM's) for one-dimensional inhomogeneous Poisson processes. The focus is on estimating the (discretized) intensity function underlying the process. Unlike the usual transform-based approach at the heart of most wavelet-based methods for Gaussian data, these BMSM's are constructed using recursive dyadic partitions (RDP's) within an entirely likelihood-based framework. Each RDP may be associated with a binary tree, and a new…
Rank Estimation of Treatment Differences Based on Repeated Measurements Subject to Dependent Censoring
依赖删失下基于重复测量的治疗差异秩估计
In comparing the effectiveness of two treatments, suppose that for each patient repeated measurements of an outcome variable are taken at prespecified time points, but some observations may be missing due to the patient's dependent right censoring. In this article, a simple rank estimation procedure, constructed based on an artificial censoring technique, is proposed for the treatment differences over time without imposing a parametric structure on the dependence between the…
A Test for Global Maximum
关于全局最大值的检验
We give simple necessary and sufficient conditions for consistency and asymptotic optimality of a root to the likelihood equation. Based on the results, a large-sample test is proposed for detecting whether a given root is consistent and asymptotically efficient, a property often possessed by the global maximizer of the likelihood function. A number of examples, and the connection between the proposed test and the test of White for model misspecification, are discussed.…
Combining Data from Polymerase Chain Reaction DNA Typing Experiments: Applications to Sperm Typing Data
合并多次PCR DNA分型实验数据:精子分型数据的应用
The polymerase chain reaction (PCR) is a procedure by which the DNA in a single cell can be made to replicate many times in a test tube. By amplifying the DNA from individual sperm cells and typing the results, estimates of male recombination fractions can be made, which are valuable for creating genetic maps and locating regions of unusually intense crossover activity on the human genome. Because PCR typing results are subject to random error, stochastic models must be…
The Inverse Gaussian Distribution: Statistical Theory and Applications
逆高斯分布:统计理论与应用
Lecture Notes in Statistic s provides a format for the informal and quick publication of monographs , cas e studies , and workshop s of theoretica l or applied importance .Thus, in some instances , proofs may be merel y outlined and result s presente d which will later be publishe d in a different form.Publication of the Lecture Notes is intende d as a service to the internationa l statistica l community , in that a commercia l publisher , Springer-Verlag , can provide…
A Modern Approach to Probability Theory
Regression Analysis of Count Data
Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics, and Population Sciences
随机转移矩阵的比较及其在信息论、统计学、经济学与人口科学中的应用
Part 1 Partial orderings among stochastic matrices, Joel E. Cohen et al: introduction notation and definitions generalizations of classical channel comparisons degradation is the same as increasing density Shannon's inclusion implies smaller capacity a simple case - matrices A and B haver only two columns open problems. Part 2 Divergence and contraction coefficients, Gh. Zbaganu: introduction, definitions and notations a generalization of an inequality of Dobrushin the…
Regression Graphics: Ideas for Studying Regression through Graphics
Tests of Linear and Logarithmic Transformations for Integrated Processes
单整过程的线性与对数变换检验
This article proposes nonnested tests of linear and logarithmic transformations of integrated processes against each other, where the innovations of both series follow autoregressive processes. It is shown that the null distributions of the test statistics for both the linear and logarithmic transformations are nonstandard when the processes have no drift, whereas they are asymptotically normal when the processes have positive drift. Monte Carlo experiments and illustrative…
Analyzing Multiple Emotions over Time by Autoregressive Negative Multinomial Regression Models
A Signal Extraction Approach to Modeling Hormone Time Series with Pulses and a Changing Baseline
含脉冲与变化基线的激素时间序列信号提取方法
Hormones serve as regulating signals for many biological processes. In recent years, it was determined that many hormones are secreted in a pulsatile manner and that the pulsatile secretion pattern, in addition to the absolute concentration level, is important in regulating biological processes. Consequently, it is necessary to characterize the latent secretion patterns from measurements of concentration levels. The characterization is complicated by the presence of a…
Multiple Confidence Sets Based on Stagewise Tests
基于逐阶段检验的多重置信集
Recent years have seen suggested constructions of multiple confidence sets related to stagewise multiple tests by some authors. These methods are a type of mixture between test and confidence interval methods, because confidence interval statements are made only for some parameters, whereas test statements for fixed parameter values are made for the other parameters. In this article I define a concept—confidence directional set—giving a confidence bound for one parameter,…
Stepwise Confidence Intervals without Multiplicity Adjustment for Dose—Response and Toxicity Studies
剂量反应与毒性研究中无需多重性调整的逐步置信区间
Not all simultaneous inferences need multiplicity adjustment. If the sequence of individual inferences is predefined, and failure to achieve the desired inference at any step renders subsequent inferences unnecessary, then multiplicity adjustment is not needed. This can be justified using the closed testing principle to test appropriate hypotheses that are nested in sequence, starting with the most restrictive one. But what hypotheses are appropriate may not be obvious in…
Extensions of Calibration Estimators in Survey Sampling
调查抽样中校准估计量的扩展
Estimators from the family of calibration estimators are often used when auxiliary information about a population is available. By viewing calibration as an algebraic problem, this article extends the calibration technique to estimate population parameters other than totals and means, and also extends the technique to the case where there is no solution to the calibration equation. These extensions permit the development of estimators for small domains that have a synthetic…
Pooled Mean Group Estimation of Dynamic Heterogeneous Panels
动态异质面板的混合均值组估计
It is now quite common to have panels in which both T, the number of time series observations, and N, the number of groups, are quite large and of the same order of magnitude. The usual practice is either to estimate N separate regressions and calculate the coefficient means, which we call the mean group (MG) estimator, or to pool the data and assume that the slope coefficients and error variances are identical. In this article we propose an intermediate procedure, the…
Filtering via Simulation: Auxiliary Particle Filters
通过模拟进行滤波:辅助粒子滤波器
This article analyses the recently suggested particle approach to filtering time series. We suggest that the algorithm is not robust to outliers for two reasons: The design of the simulators and the use of the discrete support to represent the sequentially updating prior distribution. Here we tackle the first of these problems.
Iterated Transformation–Kernel Density Estimation
迭代变换与核密度估计
Transformation from a parametric family can improve the performance of kernel density estimation. In this article we give two data-driven estimators for the optimal transformation parameter. We demonstrate that multiple families of transformations can be used at the same time, and there can be benefits to iterating this process. The transformation scheme can be expected to first pick the right transformation family and then pick the optimal parameter. Insight as to the…
On Subsampling Estimators with Unknown Rate of Convergence
Bayesian Morphology: Fast Unsupervised Bayesian Image Analysis
贝叶斯形态学:快速无监督贝叶斯图像分析
We consider the problems of image segmentation and classification, and image restoration when the true image is made up of a small number of (unordered) colors. Our emphasis is on both performance and speed; speed has become increasingly important for analyzing large images and multispectral images with many bands, processing large image databases, real-time or near realtime image analysis, and the online analysis of video. Bayesian image analysis provides an elegant…