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日期精度:到日 2273 篇 · 到月 7743 篇 · 到年 0 篇
How Much Better are Better Estimators of a Normal Variance
K -Sample Anderson–Darling Tests
多样本 Anderson–Darling 检验
Two k-sample versions of an Anderson–Darling rank statistic are proposed for testing the homogeneity of samples. Their asymptotic null distributions are derived for the continuous as well as the discrete case. In the continuous case the asymptotic distributions coincide with the (k – 1)-fold convolution of the asymptotic distribution for the Anderson–Darling one-sample statistic. The quality of this large sample approximation is investigated for small samples through Monte…
Comparison of Several Treatments with a Control Using Multiple Contrasts
用多重对比比较若干处理与对照
A problem frequently encountered in the practice of statistics is the comparison of several treatments with a control or standard. We consider an experimental situation where prior knowledge indicates that all of the treatments are at least as effective as the control and the problem is to determine if any are significantly better than the control. A number of statistical procedures have been proposed for this situation, of which the best known is Dunnett's (1955) multiple…
Minimax Regret Simultaneous Confidence Bands for Multiple Regression Functions
Model Robustness for Simultaneous Confidence Bands
同时置信带对模型误设的稳健性
Confidence bands for the simple linear model are examined to assess their degrees of robustness to departures from the model. All calculations are made under an interval constraint on the range of interest for the predictor variable. The true model is taken to be a quadratic polynomial, and departure from the linear case is considered in terms of increasing magnitude of a curvature parameter. Proposed measures of robustness include the actual coverage probability under the…
A Semiparametric Approach to Density Estimation
密度估计的半参数方法
One method of fitting a parametric density function f(x, θ) is first to estimate θ by maximum likelihood, say, and then to estimate f(x, θ) by . On the other hand, when the parametric model does not hold, the true density f(x) may be estimated nonparametrically, as in the case of a kernel estimate . The key idea proposed is to fit a combination of the parametric and nonparametric estimates, namely where π (0 ≤ π ≤ 1) is unknown. The parameter π is estimated from the data,…
Marginal Curvatures and Their Usefulness in the Analysis of Nonlinear Regression Models
Regression Methods for Poisson Process Data
泊松过程数据的回归方法
This article is directed toward situations where individuals can experience repeated events, and data on an individual consist of the number and occurrence times of events, along with concomitant variables. Methods of regression analysis are presented, based on Poisson process and proportional intensity assumptions. These include parametric and semi-parametric approaches to model fitting, model assessment, and the treatment of random effects. In addition, insight is gained…
Minimum Hellinger Distance Estimation for the Analysis of Count Data
计数数据分析中的最小 Hellinger 距离估计
Minimum Hellinger distance (MHD) estimation is studied in the context of discrete data. The MHD estimator is shown to provide an effective treatment of anomalous data points, and its properties are illustrated using short-term mutagenicity test data. Asymptotic normality for a discrete distribution with countable support is derived under a readily verified condition on the model. Breakdown properties of the MHD estimator and an outlier screen are compared. Count data occur…
Time- and Space-Efficient Algorithms for Least Median of Squares Regression
最小平方残差中位数回归的时间与空间高效算法
The least median of squared residuals regression line (or LMS line) is that line y = ax + b for which the median of the residuals |yi - axi - b |2 is minimized over all choices of a and b. If we rephrase the traditional ordinary least squares (OLS) problem as finding the a and b that minimize the mean of | yi - axi - b |2, one can see that in a formal sense LMS just replaces a “mean” by a “median.” This way of describing LMS regression does not do justice to the remarkable…
Bayesian Methods for Censored Categorical Data
An Application of Bayes Methodology to the Analysis of Diary Records from a Water Use Study
贝叶斯方法在家庭用水日记分析中的应用
One of the objectives of a comprehensive domestic water use study conducted in Perth, Western Australia, was the quantification of components of water usage. Each household in a sample of about 3,000 was asked to record all water uses in a specially provided diary for a 2-week period, and the total water usage, both in-house and ex-house, was metered daily during this time. This article describes an application of Bayesian methodology to the estimation of usage for each…
Parameter Estimation for the Sichel Distribution and its Multivariate Extension
Sichel 分布及其多元扩展的参数估计
The Sichel distribution is a three-parameter compound Poisson distribution. It is a versatile model for highly skewed frequency distributions of observed counts and has proved useful in fields as diverse as mining engineering, linguistics, ecology, industrial psychology, and market research. We propose a reparameterization of the Sichel distribution and give an algorithm, which can be implemented on a typical desktop microcomputer, for computing the maximum likelihood…
Small Sample Properties of Probit Model Estimators
Probit 模型估计量的小样本性质
When maximum likelihood estimates of the coefficients in a nonlinear model such as the probit model are obtained there are a number of asymptotically equivalent covariance matrix estimators that can be used. These covariance matrix estimators are typically associated with different computer algorithms. For example, with the Newton–Raphson algorithm the inverse of the negative of the Hessian matrix from the log-likelihood function is used; with the method of scoring the…
Influence Analysis of Generalized Least Squares Estimators
广义最小二乘估计量的影响分析
Influence analysis and leverage analysis are important and well-established adjuncts to ordinary least squares (OLS) regression, but analogous regression diagnostics are not generally available for multivariate regression problems. This article describes measures of influence and leverage for a generalized least squares (GLS) estimator of the regression coefficients in a class of multivariate linear models for repeated measurements. When the covariance matrix of the…
Best Median-Unbiased Estimation in Linear Regression with Bounded Asymmetric Loss Functions
有界非对称损失下线性回归的最优中位数无偏估计
This article considers optimal median-unbiased estimation in a linear regression model with the distribution of the errors lying in a subclass of the elliptically symmetric distributions. The generalized least squares (GLS) estimator is shown to be best for any monotone loss function, that is, any loss function that is nondecreasing as the magnitude of underestimation or overestimation increases. This includes bounded asymmetric loss functions. For the same loss functions, a…
Quick Simultaneous Confidence Intervals for Multinomial Proportions
多项比例的快速同时置信区间
Opinion polls often give an indication of sampling error based on the standard conservative confidence intervals for a single binomial proportion. We give a lower bound for the simultaneous coverage probability when such intervals are applied to all of the proportions in a poll. This bound is equal to 1 – 2α. for small values of α. The same result is shown to apply to the standard confidence intervals for changes in proportions between surveys.
A Comparison of Variance Component Estimates for Arbitrary Underlying Distributions
任意底层分布下方差分量估计的比较
Large-sample covariance matrices for the analysis of variance (ANOVA), minimum norm quadratic unbiased estimator (MINQUE), restricted maximum likelihood (REML), and maximum likelihood (ML) estimates of variance components are presented for the unbalanced one-way model when the underlying distributions are not necessarily normal. The limiting variances depend on the design sequence, on the actual values of the variance components, and on the kurtosis parameters of the…
L -Estimation for Linear Models
线性模型的 L 估计
Linear combinations of order statistics, or L-estimators, have played an extremely important role in the development of robust methods for the one-sample problem. We suggest analogs of L-estimators for the parameters of the linear model based on the p-dimensional “regression quantiles” proposed by Koenker and Bassett (1978). A uniform, Bahadur-type asymptotic representation of regression quantiles is established, and this yields a general asymptotic theory of L-estimators…
Identifying a Simplifying Structure in Time Series
识别时间序列中的简化结构
This article studies how to identify hidden factors in multivariate time series process. This problem is important because, when the series are driven by a set of common factors, (a) a large number of parameters may be needed to obtain an adequate representation of the system and (b) the estimated parameters will be highly correlated. Therefore, a complex and badly defined relationship can appear when, in fact, a simpler and parsimonious model in terms of a few common…
A Frequency-Domain Median Time Series
频域中位数时间序列
This article discusses the median of a batch of time series. We focus on the frequency-domain median (FDM) series (Zeger 1985), which is calculated from the “mediancenters” (Gower 1974) of the discrete Fourier transforms. Like the univariate median, it has a breakdown value of 50%. Like the mean, the FDM time series of independent realizations from a stationary Gaussian process has a spectrum proportional to that of the component series. Analogs of the univariate median have…
Conditioning Ratio Estimates under Simple Random Sampling
简单随机抽样下比率估计的条件化调整
The usual ratio estimates for a population mean use information on an auxiliary variable to improve the estimation. The standard randomization analysis, however, does not take enough account of the observations on the auxiliary variable, so estimates and estimated variates can be conditionally biased unless the sample is balanced with respect to the auxiliary variable. I propose a method of adjustment for the bias of the estimate and its variance based only on the assumption…
Test Statistics Derived as Components of Pearson's Phi-Squared Distance Measure
由Pearson平方距离分量导出的检验统计量
A general approach to the comparison of two absolutely continuous distributions is presented based on Pearson's θ2 measure. Although no simple estimates are available for θ2, it can be decomposed into components, all of which are easily estimated. Asymptotic distribution theory is derived for the component estimates, and the form of the components is considered for several standard problems. It is demonstrated that the components-of-θ2 approach provides a unified approach to…