日期精度：到日 2271 篇 · 到月 7741 篇 · 到年 0 篇
利用广义 Savage–Dickey 密度比计算贝叶斯因子
We present a simple method for computing Bayes factors. The method derives from observing that in general, a Bayes factor can be written as the product of a quantity called the Savage-Dickey density ratio and a correction factor; both terms are easily estimated from posterior simulation. In some cases it is possible to do these computations without ever evaluating the likelihood.
稳定分布的贝叶斯推断
Very little work on stable distribution parameter estimation and inference appears in the literature due to the nonexistence of the probability density function. This has led in particular to a dearth of Bayesian work in this area. But Bayesian computation via Markov chain Monte Carlo allows us to sample from the distribution of the parameters of the stable distributions, by exploiting a particular mathematical representation involving the stable density.
线性回归模型中对称性的一致非参数检验
This article proposes a consistent nonparametric test of the hypothesis that the disturbance in a linear regression model is distributed symmetrically around zero. Simulation results show that the test has good size and power properties for sample sizes as small as 50. We illustrate the use of the test in a cross-country model of inflation and monetary growth.
二元回归测量误差模型中的工具变量估计
We describe two approaches to instrumental variable estimation in binary regression measurement error models. The methods entail constructing approximate mean models for the binary response as a function of the measured predictor, the instrument, and any covariates in the model. Estimates are obtained by exploiting relationships between regression parameters, just as in linear instrumental variable estimation. In the course of deriving the approximate mean models, we obtain…
有序分类数据的随机效应模型
This article presents a random-effects model for multivariate and grouped univariate ordered categorical data. The assumed family of distributions for the random effects adopts a wide variety of forms and shapes. The model's likelihood has a closed expression and can be computed without recourse to numerical integration or Gaussian quadrature. A bivariate and a grouped univariate example are used to illustrate the proposed model.
部分因子实验中删失数据的贝叶斯分析
Censored data arise naturally in industrial experiments whose observations are failure times or measurements with mixed continuous-categorical outcomes. When censored data are observed from a fractionated experiment, likelihood-based estimates quite often do not exist, especially when the opportunity for improvement is great. To circumvent this problem, we propose a Bayesian analysis strategy that has a straightforward implementation using the data augmentation and Monte…
超额收益的条件分布：一项实证分析
In this article we describe the cumulative distribution function of excess returns conditional on a broad set of predictors that summarize the state of the economy. We do so by estimating a sequence of conditional logit models over a grid of values of the response variable. Our method uncovers higher-order multidimensional structure that cannot be found by modeling only the first two moments of the distribution. We compare two approaches to modeling: one based on a…
可变处理强度模型中平均因果效应的两阶段最小二乘估计
Two-stage least squares (TSLS) is widely used in econometrics to estimate parameters in systems of linear simultaneous equations and to solve problems of omitted-variables bias in single-equation estimation. We show here that TSLS can also be used to estimate the average causal effect of variable treatments such as drug dosage, hours of exam preparation, cigarette smoking, and years of schooling. The average causal effect in which we are interested is a conditional…
贝叶斯因子
In a 1935 paper and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null is one-half. Although there has been much discussion of Bayesian hypothesis testing in the context of criticism of P-values, less attention has been given to the Bayes factor as a…
偏态分布均值的检验
Johnson proposed some modified t tests to assess the mean of asymmetrical distributions. The tests were suggested for any parent distribution ranging from the normal to a distribution as asymmetric as an exponential distribution for sample sizes as small as 13. In many practical situations the skewness of the parent distribution can be greater than those studied by Johnson and the sample sizes can be quite small, possibly as small as 10, due to the cost of the sampling…
多个二元结局检验的效率与功效
Global tests provide a useful tool for comparing two or more groups with respect to multiple correlated outcomes. We adapt and compare the performance of tests that have been suggested for use with multiple continuous outcomes to the case of multiple binary outcomes. Comparisons and guidelines are based on asymptotic relative efficiencies (ARE's) and simulations. These results are illustrated using an application from teratology. We extend the work of Lefkopoulou and Ryan to…
尺度变换随机效应模型的生存分析
Frailty models are effective in broadening the class of survival models and inducing dependence in multivariate survival distributions. In proportional hazards, the random effect multiplies the hazard function. The scale-change model incorporates unobserved heterogeneity through a random effect that enters the baseline hazard function to change the time scale. We interpret this random effect as frailty, or other unobserved risks that create heterogeneity in the population.…
信息可区分性及其在失效数据分析中的应用
In maximum entropy (ME) modeling, the information discrepancy between two distributions is measured in terms of their entropy difference. In discrimination information statistics the information discrepancy between two distributions is measured in terms of the Kullback-Leibler function (i.e., relative entropy or cross-entropy). This article presents an equivalence between Kullback–Leibler functions and entropy differences involving an ME distribution. Based on this…
用于 K 个 2×J 列联表的投影法 Mantel–Haenszel 估计量
A projection method is introduced to generalize the Mantel-Haenszel estimator for estimating the common odds ratios in K 2 × J (J > 2) tables. The method provides estimators in an explicit form and needs no iterative computation. It is shown that the generalized Mantel-Haenszel estimator proposed by Greenland, and Yanagawa and Fujii is obtained by this method as a special case. Furthermore, selecting appropriate weight, it is shown that the method leads to an estimator that…
通过控制变量法估计精确 p 值：蒙特卡洛救援
Despite algorithmic advances in exact nonparametric inference, problems often occur that are too large for exact p value computations but too sparse for reliable asymptotic results. In these situations Monte Carlo methods are a good compromise. They bound the true p value within a confidence interval. But a factor discouraging the use of Monte Carlo p values is their sensitivity to the random number sequence. One can overcome this drawback by computing a 99% C.I. confidence…
三维列联表条件关联的改进精确推断
We propose modified exact inferential methods for contingency tables. Ordinary “exact” inference is conservative, because of the discreteness. For estimating a common odds ratio in several 2 × 2 tables, two modifications of the ordinary “exact” confidence interval maintain at least a fixed confidence level but tend to be much narrower. One approach inverts results of a test with a modified P value utilizing the test statistic and table probabilities. The second approach…
正态均值乘积的参考先验贝叶斯分析
Two reference priors for the product of means of n normal distributions with common known variance are developed. One of them induces an improper posterior distribution and therefore is not of much interest. The other is a generalized form of the n = 2 case derived by Berger and Bernardo. The latter is compared with the uniform prior (the Jeffreys prior) in posterior inference and the optimal frequentist coverage criterion. The reference prior is shown to be better than the…
利用混合模型进行贝叶斯密度估计与推断
We describe and illustrate Bayesian inference in models for density estimation using mixtures of Dirichlet processes. These models provide natural settings for density estimation and are exemplified by special cases where data are modeled as a sample from mixtures of normal distributions. Efficient simulation methods are used to approximate various prior, posterior, and predictive distributions. This allows for direct inference on a variety of practical issues, including…
通过序贯插补进行盲反卷积
The sequential imputation procedure is applied to adaptively and sequentially reconstruct discrete input signals that are blurred by an unknown linear moving average channel and contaminated by additive Gaussian noises, a problem known as blind deconvolution in digital communication. A rejuvenation procedure for improving the efficiency of sequential imputation is introduced and theoretically justified. The proposed method does not require the channel to be nonminimum phase…
马尔可夫链蒙特卡洛的下界条件与收敛速度
General methods are provided for analyzing the convergence of discrete-time, general state-space Markov chains, such as those used in stochastic simulation algorithms including the Gibbs sampler. The methods provide rigorous, a priori bounds on how long these simulations should be run to give satisfactory results. Results are applied to two models of the Gibbs sampler: a bivariate normal model, and a hierarchical Poisson model (with gamma conditionals). The methods use the…
核回归的自适应带宽选择
A data-based procedure is introduced for local bandwidth selection for kernel estimation of a regression function at a point. The estimated bandwidth is shown to be consistent and asymptotically normal as an estimator of the (asymptotic) optimal value for minimum mean square estimation. Simulation studies indicate satisfactory behavior of the new bandwidth estimator in finite samples. The findings are improvements over a global bandwidth estimator. The same methodology works…
两侧变换回归模型中变换函数的非参数估计
The transform-both-sides (TBS) regression model developed by Carroll and Ruppert is applicable when the relationship between the median response and the independent variables has been identified. Several different families of transformations, such as the Box-Cox power family, have been considered in the parametric approach to this model. In this article, we propose a nonparametric estimator of the transformation in the TBS model allowing general smooth monotonic…
分布函数的非参数似然置信带
Berk and Jones described a nonparametric likelihood test of uniformity with greater asymptotic Bahadur efficiency than any weighted Kolmogorov–Smirnov test at any alternative to U[0, 1]. We invert this test to form confidence bands for a distribution function using Noé's recursion. Nonparametric likelihood bands are narrower in the tails and wider in the center than Kolmogorov-Smirnov bands and are asymmetric about the empirical cumulative distribution function. This article…