日期精度：到日 3 篇 · 到月 8 篇 · 到年 11 篇
计量经济学、金融及其他领域中的时间序列模型
Statistical Aspects of ARCH and Scholastic Volatility Likelihood-Based Inference for Cointegration of Some Non-Stationary Time Series Forecasting in Macroeconomics Longitudinal Panel Data: An Overview of Current Methodology
利用非参数曲线进行模型检验
The use of local likelihood curve estimates in model checking is described. Test statistics are based on deviance differences, and are interpreted using nonparametric bootstrap Monte Carlo. Some theoretical aspects are discussed. Methods are illustrated for regression with discrete data.
利用非参数曲线进行模型检验
The use of local likelihood curve estimates in model checking is described. Test statistics are based on deviance differences, and are interpreted using nonparametric bootstrap Monte Carlo. Some theoretical aspects are discussed. Methods are illustrated for regression with discrete data.
Bootstrap模拟的平衡设计
SUMMARY Davison et al. (1986) have shown that finite bootstrap simulations can be improved by forcing balance in the aggregate of simulated data sets. Their methods yield first-order balance, which principally affects bootstrap estimation of bias. Here we extend the methodology to second-order balance, which principally affects bootstrap estimation of variance. The particular techniques involve Latin square and balanced incomplete block designs. Numerical examples are given…
重要性抽样与嵌套 bootstrap
The nested bootstrap is a computer-intensive technique for reducing the statistical error in the ordinary bootstrap. We show how the Monte Carlo technique of importance sampling can be used to substantially reduce the amount of computation needed in a simple double bootstrap confidence limit method.
重要性抽样与嵌套自助法
The nested bootstrap is a computer-intensive technique for reducing the statistical error in the ordinary bootstrap. We show how the Monte Carlo technique of importance sampling can be used to substantially reduce the amount of computation needed in a simple double bootstrap confidence limit method.
关于回归变换得分检验的进一步研究
Lawrance's (1987) results concerning tests for transformation in regression are extended to models where response and mean may both be transformed. It is also suggested (i) that the methods of Lawrance and of Atkinson (1982) lead to statistics with near-perfect correlation, and (ii) that observed and expected informations may have considerably different effects as standardizations of the score statistic.
回归变换得分检验的进一步讨论
Lawrance's (1987) results concerning tests for transformation in regression are extended to models where response and mean may both be transformed. It is also suggested (i) that the methods of Lawrance and of Atkinson (1982) lead to statistics with near-perfect correlation, and (ii) that observed and expected informations may have considerably different effects as standardizations of the score statistic.
高效自助法模拟
Bootstrap methods are simulation methods for assessing sampling properties of statistical estimates. We discuss two ideas for making the simulation more efficient. The first idea is to balance the simulated samples, and the second idea is to make explicit use approximations which do not require simulation. Both ideas are illustrated with three examples.
作为近似枢轴分布的似然
For a single-parameter curved exponential family, it is shown that the conditional distribution of the maximum likelihood estimator is the normalized likelihood function, except for a relative error proportional to inverse sample size.
位置与尺度参数的似然推断
We obtain a normal approximation to the conditional distribution of maximum likelihood estimates in location-scale families. The covariance matrix is the inverse of minus the observed log likelihood second derivative matrix at the likelihood maximum, as opposed to the inverse of Fisher information, to which it is superior. Confidence intervals for the location parameter are discussed. Small sample numerical results are given for the Cauchy case to illustrate the accuracy of…
已知变异系数时关于正态均值的条件推断
For a random sample from the normal distribution with known coefficient of variation, the minimal sufficient statistic includes an ancillary statistic. The effects of conditioning on the ancillary statistic are discussed and related to a recommendation of R. A. Fisher concerning use of the observed second derivative of the log likelihood function in normal approximations.
已知变异系数时正态均值的条件推断
For a random sample from the normal distribution with known coefficient of variation, the minimal sufficient statistic includes an ancillary statistic. The effects of conditioning on the ancillary statistic are discussed and related to a recommendation of R. A. Fisher concerning use of the observed second derivative of the log likelihood function in normal approximations.
基于累积和检验的变点推断
The point of change in mean in a sequence of normal random variables can be estimated from a cumulative sum test scheme. The asymptotic distribution of this estimate and associated test statistics are derived and numerical results given. The relation to likelihood inference is emphasized. Asymptotic results are compared with empirical sequential results, and some practical implications are discussed.
两阶段回归模型交点的统计推断
We study the problem of estimating and making inferences about the intersection in a two-phase regression model with one independent variable. In particular we derive an asymptotic distribution for the maximum likelihood estimate of the intersection which is a good finite sample approximation. We also discuss the associated problems of testing hypotheses about the intersection.
关于最小二乘估计效率的一则札记
Summary A linear model is considered in which errors are independent and identically distributed with zero mean. If the error distribution is specified, except possibly for unknown parameters, the asymptotic efficiency of least-squares estimates relative to maximum-likelihood estimates can be found. For regression parameters orthogonal to the general mean the asymptotic efficiency, which is independent of the design matrix, is calculated explicitly for an Edgeworth series,…