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针对单侧截断正态备择的指数分布最优检验AI 解读

We show that the likelihood ratio test of exponentiality against singly truncated normal alternatives is the uniformly most powerful unbiased test and can be expressed in terms of the sampling coefficient of variation. This test is closely related to Greenwood's statistic for testing departures from the uniform distribution. We provide a way to approximate the critical points of the test, using saddlepoint methods, that gives a high degree of accuracy.

可靠性理论与生存分析中的不变指数模型AI 解读

For a two-parameter exponential model with increasing failure rate (IFR) or decreasing failure rate (DFR) distributions necessary and sufficient conditions of the existence of a solution of the likelihood equations are given. Also, all of the scale-invariant two-parameter statistical models closed by raising to a power and by exponential tilting are introduced. The conditions of existence of a solution of the likelihood equations are studied for these invariant models, and…

删失生存数据随机提前终止的一般理论AI 解读

Stochastic curtailment is a valuable tool in monitoring long-term medical studies. Under this approach, one calculates the conditional power, which is the probability of rejecting the null hypothesis at the scheduled end of the study given the existing data at the interim analysis, along with certain speculation about the future data. The conditional power may be used to aid the decision to terminate a study prematurely or to extend a study beyond its originally planned…

竞争风险子分布的比例风险模型AI 解读

With explanatory covariates, the standard analysis for competing risks data involves modeling the cause-specific hazard functions via a proportional hazards assumption. Unfortunately, the cause-specific hazard function does not have a direct interpretation in terms of survival probabilities for the particular failure type. In recent years many clinicians have begun using the cumulative incidence function, the marginal failure probabilities for a particular cause, which is…

三条及以上回归直线所有对比的精确置信界AI 解读

It is desired to compare κ ≥ 3 treatments. Under the assumption of iid normal errors, it is well known that the Scheffé method produces exact simultaneous confidence bounds for all contrasts of the treatment means. Furthermore, it is known that the Scheffé method is conservative when one desires confidence bounds for a specific subset of contrasts of means. Exact methods, such as those due to Tukey and Dunnett, yield tighter bounds than the Scheffé method for specific…

自洽性与主成分分析AI 解读

I examine the self-consistency of a principal component axis; that is, when a distribution is centered about a principal component axis. A principal component axis of a random vector X is self-consistent if each point on the axis corresponds to the mean of X given that X projects orthogonally onto that point. A large class of symmetric multivariate distributions are examined in terms of self-consistency of principal component subspaces. Elliptical distributions are…

预测区间、因子分析模型与高维经验线性预测AI 解读

We discuss a technique that provides prediction intervals based on a model called an empirical linear model. The technique, high-dimensional empirical linear prediction (HELP), involves principal component analysis, factor analysis and model selection. In fact, a special case of the empirical model is the factor analysis model. A factor analysis model does not generally aim at prediction, however. Therefore, HELP can be viewed as a technique that provides prediction (and…

大型回归问题中的快速离群诊断程序AI 解读

We propose a procedure for computing a fast approximation to regression estimates based on the minimization of a robust scale. The procedure can be applied with a large number of independent variables where the usual algorithms require an unfeasible or extremely costly computer time. Also, it can be incorporated in any high-breakdown estimation method and may improve it with just little additional computer time. The procedure minimizes the robust scale over a set of…

回归深度AI 解读

In this article we introduce a notion of depth in the regression setting. It provides the “rank” of any line (plane), rather than ranks of observations or residuals. In simple regression we can compute the depth of any line by a fast algorithm. For any bivariate dataset Z n of size n there exists a line with depth at least n/3. The largest depth in Z n can be used as a measure of linearity versus convexity. In both simple and multiple regression we introduce the deepest…

脑电轨迹的评估与比较：非平稳时间序列中的潜在结构AI 解读

We explore and illustrate the use of time series decomposition methods for evaluating and comparing latent structure in nonstationary electroencephalographic (EEG) traces obtained from depressed patients during brain seizures induced as part of electroconvulsive therapy (ECT). Analysis of the patterns of change over time in the frequency structure of such EEG data provides insight into the neurophysiological mechanisms of action of this effective but poorly understood…

通过统计方法改进质量AI 解读

Process description, 62 6.2.2 Model formulation and fitting, 63 6.3 EPC Component: Developing the Control Rule, 63 6.3.1 The Minimum Mean Square Error Controller (MMSEC),64 6.3.2The Two-Step Ahead Forecasting Controller (TSAFC),64 6.3.3Clarke's Constrained Controller (CCC(r)), 65 6.4 Comparison of Control Strategies, 66 6.5 Robustness Properties of the Controllers, 67 6.6 EPC Component: Performance Under Assignable Causes, 69 6.7 SPC Component: Developing Monitoring…

重尾实用指南：统计技术与应用AI 解读

Part 1 Applications: heavy tailed probability distributions in the World Wide Web, M.E. Crovella et al self-similarity and heavy tails - structural modelling of network traffic, W. Willinger et al heavy tails in high-frequency financial data, U.A. Muller et al stable paretian modelling in finance - some empirical and theoretical aspects, S. Mittnik et al risk management and quantile estimation, F. Bassi et al. Part 2 Time series: analyzing stable time series, R.J. Adler et…

动态非线性计量经济模型：渐近理论AI 解读

1 Introduction.- 2 Models, Data Generating Processes, and Estimators.- 3 Basic Structure of the Classical Consistency Proof.- 4 Further Comments on Consistency Proofs.- 5 Uniform Laws of Large Numbers.- 6 Approximation Concepts and Limit Theorems.- 7 Consistency: Catalogues of Assumptions.- 8 Basic Structure of the Asymptotic Normality Proof.- 9 Asymptotic Normality under Nonstandard Conditions.- 10 Central Limit Theorems.- 11 Asymptotic Normality: Catalogues of…

渐近推断的几何基础AI 解读

Overview and Preliminaries. ONE-PARAMETER CURVED EXPONENTIAL FAMILIES. First-Order Asymptotics. Second-Order Asymptotics. MULTIPARAMETER CURVED EXPONENTIAL FAMILIES. Extensions of Results from the One-Parameter Case. Exponential Family Regression and Diagnostics. Curvature in Exponential Family Regression. DIFFERENTIAL-GEOMETRIC METHODS. Information-Metric Riemannian Geometry. Statistical Manifolds. Divergence Functions. Recent Developments. Appendices. References. Indexes.

摘要暂缺

删失生存数据随机提前终止的一般理论AI 解读

Stochastic curtailment is a valuable tool in monitoring long-term medical studies. Under this approach, one calculates the conditional power, which is the probability of rejecting the null hypothesis at the scheduled end of the study given the existing data at the interim analysis, along with certain speculation about the future data. The conditional power may be used to aid the decision to terminate a study prematurely or to extend a study beyond its originally planned…

基于分阶段检验的多重置信集AI 解读

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,…

三条及以上回归直线所有对比的精确置信界AI 解读

It is desired to compare κ ≥ 3 treatments. Under the assumption of iid normal errors, it is well known that the Scheffé method produces exact simultaneous confidence bounds for all contrasts of the treatment means. Furthermore, it is known that the Scheffé method is conservative when one desires confidence bounds for a specific subset of contrasts of means. Exact methods, such as those due to Tukey and Dunnett, yield tighter bounds than the Scheffé method for specific…

摘要暂缺

大型回归问题中异常值诊断的快速程序AI 解读

We propose a procedure for computing a fast approximation to regression estimates based on the minimization of a robust scale. The procedure can be applied with a large number of independent variables where the usual algorithms require an unfeasible or extremely costly computer time. Also, it can be incorporated in any high-breakdown estimation method and may improve it with just little additional computer time. The procedure minimizes the robust scale over a set of…

脑电轨迹的评估与比较：非平稳时间序列中的潜在结构AI 解读

We explore and illustrate the use of time series decomposition methods for evaluating and comparing latent structure in nonstationary electroencephalographic (EEG) traces obtained from depressed patients during brain seizures induced as part of electroconvulsive therapy (ECT). Analysis of the patterns of change over time in the frequency structure of such EEG data provides insight into the neurophysiological mechanisms of action of this effective but poorly understood…

非线性回归的渐近理论AI 解读

Introduction. 1. Consistency. 2. Approximation by a Normal Distribution. 3. Asymptotic Expansions Related to the Least Squares Estimator. 4. Geometric Properties of Asymptotic Expansions. Appendix: I: Subsidiary Facts. II: List of Principal Notations. Commentary. Bibliography. Index.

语音识别的统计方法AI 解读

The speech recognition problem hidden Markov models the acoustic model basic language modelling the Viterbi search hypothesis search on a tree and the fast match elements of information theory the complexity of tasks - the quality of language models the expectation - maximization algorithm and its consequences decision trees and tree language models phonetics from orthography - spelling-to-base from mappings triphones and allophones maximum entropy probability estimation and…

摘要暂缺