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扩散过程模型设定检验AI 解读

We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the transitional density of the process. The empirical likelihood is used to formulate a statistic, for each kernel smoothing bandwidth, which is effectively a Studentized L2-distance between the kernel transitional density estimator and the parametric transitional density implied by the parametric process. To reduce the sensitivity of the test on smoothing bandwidth…

非平稳波动率时间序列的自助法单位根检验AI 解读

The presence of permanent volatility shifts in key macroeconomic and financial variables in developed economies appears to be relatively common. Conventional unit root tests are unreliable in the presence of such behavior, having nonpivotal asymptotic null distributions. In this paper we propose a bootstrap approach to unit root testing that is valid in the presence of a wide class of permanent variance changes that includes single and multiple (abrupt and smooth transition)…

学生化与准确 p 值的推导AI 解读

We have a statistic for assessing an observed data point relative to a statistical model but find that its distribution function depends on the parameter. To obtain the corresponding p-value, we require the minimally modified statistic that is ancillary; this process is called Studentization. We use recent likelihood theory to develop a maximal third-order ancillary; this gives immediately a candidate Studentized statistic. We show that the corresponding p-value is…

大规模面板中的斜率同质性检验AI 解读

This paper proposes a modified version of Swamy’s test of slope homogeneity for panel data models where the cross section dimension (N) could be large relative to the time series dimension (T). We exploit the cross section dispersion of individual slopes weighted by their relative precision. Using Monte Carlo experiments, we show that the test has the correct size and satisfactory power in panels with strictly exogenous regressors for various combinations of N and T. For…

稳健非嵌套检验与货币需求AI 解读

Nonnested hypothesis testing procedures recently have been extended to dynamic nonnested models. We propose robust tests that generalize the J test and the F test for nonnested dynamic models with unknown serial correlation and conditional heteroscedasticity in errors and regressors. We investigate the finite-sample properties of our test statistics and propose to use bootstrap methods or the fixed-b asymptotics developed by Kiefer and Vogelsang to improve the asymptotic…

匹配估计量的 bootstrap 失效问题AI 解读

Matching estimators are widely used in empirical economics for the evaluation of programs or treatments. Researchers using matching methods often apply the bootstrap to calculate the standard errors. However, no formal justification has been provided for the use of the bootstrap in this setting. In this article, we show that the standard bootstrap is, in general, not valid for matching estimators, even in the simple case with a single continuous covariate where the estimator…

关于《含单位根的门限自回归》的评论AI 解读

In this paper we revisit the results in Caner and Hansen (2001), where the authors obtained novel limiting distributions of Wald type test statistics for testing for the presence of threshold nonlinearities in autoregressive models containing unit roots. Using the same framework, we obtain a new formulation of the limiting distribution of the Wald statistic for testing for threshold effects, correcting an expression that appeared in the main theorem presented by Caner and…

协变量含测量误差时多项式模型的适用性检验AI 解读

A low-degree polynomial model for a response curve is used commonly in practice. It generally incorporates a linear or quadratic function of the covariate. In this paper we suggest methods for testing the goodness of fit of a general polynomial model when there are errors in the covariates. There, the true covariates are not directly observed, and conventional bootstrap methods for testing are not applicable. We develop a new approach, in which deconvolution methods are used…

摘要暂缺

协变量随机缺失回归模型的筛极大似然估计AI 解读

Missing covariates are common in regression problems. We propose a new semiparametric method based on a fully nonparametric distribution for the missing covariates that are assumed to be missing at random. The method of sieve maximum likelihood estimation is used to obtain the estimators of the regression coefficients. These estimators are shown to be consistent and asymptotically normal with their asymptotic covariance matrix that achieves the semiparametric efficiency…

正态、Student t与bootstrap校准可支持多少个同时假设检验？AI 解读

In the analysis of microarray data, and in some other contemporary statistical problems, it is not uncommon to apply hypothesis tests in a highly simultaneous way. The number, N say, of tests used can be much larger than the sample sizes, n, to which the tests are applied, yet we wish to calibrate the tests so that the overall level of the simultaneous test is accurate. Often the sampling distribution is quite different for each test, so there may not be an opportunity to…

非齐次空间点模式的稀疏化分块自助方差估计AI 解读

When modeling inhomogeneous spatial point patterns, it is of interest to fit a parametric model for the first-order intensity function (FOIF) of the process in terms of some measured covariates. Estimates for the regression coefficients, say , can be obtained by maximizing a Poisson maximum likelihood criterion. Little work has been done on the asymptotic distribution of except in some special cases. In this article we show that is asymptotically normal for a general class…

基于最小角回归的稳健线性模型选择AI 解读

In this article we consider the problem of building a linear prediction model when the number of candidate predictors is large and the data possibly contain anomalies that are difficult to visualize and clean. We want to predict the nonoutlying cases; therefore, we need a method that is simultaneously robust and scalable. We consider the stepwise least angle regression (LARS) algorithm which is computationally very efficient but sensitive to outliers. We introduce two…

由纵向分类数据估计事件发生时间AI 解读

The expanded disability status scale (EDSS) is an ordinal score that measures progression in multiple sclerosis (MS). Progression is defined as reaching EDSS of a certain level (absolute progression) or increasing of one point of EDSS (relative progression). Survival methods for time to progression are not adequate for such data since they do not exploit the EDSS level at the end of follow-up. Instead, we suggest a Markov transitional model applicable for repeated…

Farrell 型效率聚合指标的统计推断AI 解读

Abstract In this study, we merge results of two recent directions in efficiency analysis research—aggregation and bootstrap—applied, as an example, to one of the most popular point estimators of individual efficiency: the data envelopment analysis (DEA) estimator. A natural context of the methodology developed here is a study of efficiency of a particular economic system (e.g., an industry) as a whole, or a comparison of efficiencies of distinct groups within such a system…

非参数回归中方差函数参数形式的新检验AI 解读

Summary In the common non-parametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes that are obtained from the standardized non-parametric residuals under the null hypothesis (of a specific parametric form of the variance function) and the alternative is introduced and its weak convergence established. This result is used for the…

摘要暂缺

多重变点问题的在线推断AI 解读

Summary We propose an on-line algorithm for exact filtering of multiple changepoint problems. This algorithm enables simulation from the true joint posterior distribution of the number and position of the changepoints for a class of changepoint models. The computational cost of this exact algorithm is quadratic in the number of observations. We further show how resampling ideas from particle filters can be used to reduce the computational cost to linear in the number of…

位置或距离测量误差下的空间相关稳健推断AI 解读

This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. We investigate the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic variances. Nonparametric estimators are quite robust to such errors, method of moments estimators perform surprisingly well, and MLE estimators are very poor. We also present and evaluate a speci...cation test based on a parametric…

利用 MCMC 实现基于估计函数的推断AI 解读

Under a semiparametric or nonparametric setting, inferences about the unknown parameter are often made based on a nonsmooth estimating function. Resampling methods are quite handy for obtaining good approximations to the distribution of the consistent estimator when the estimating equation and its resampled counterparts are not difficult to solve numerically. In this article we propose a simple, flexible procedure that provides such approximations through the standard Markov…

自回归模型中的一致有效推断AI 解读

The purpose of this paper is to provide theoretical justification for some existing methods for constructing confidence intervals for the sum of coefficients in autoregressive models. We show that the methods of Stock (1991), Andrews (1993), and Hansen (1999) provide asymptotically valid confidence intervals, whereas the subsampling method of Romano and Wolf (2001) does not. In addition, we generalize the three valid methods to a larger class of statistics. We also clarify…

利用 Gibbs 抽样获得条件检验及其应用AI 解读

A random sample is drawn from a distribution which admits a minimal sufficient statistic for the parameters. The Gibbs sampler is proposed to generate samples, called conditionally sufficient or co-sufficient samples, from the conditional distribution of the sample given its value of the sufficient statistic. The procedure is illustrated for the gamma distribution. Co-sufficient samples may be used to give exact tests of fit; for the gamma distribution these are compared for…

Aalen 加性风险变点模型AI 解读

We study a test comparing the full Aalen additive hazards model and the change-point model, and suggest how to estimate the parameters of the change-point model. We also study a test for no change-point effect. Both tests are provided with large sample properties and a resampling method is applied to obtain p-values. The finite-sample properties of the proposed inference procedures and estimators are assessed through a simulation study. The methods are further applied to a…

加权对数秩置换检验：用鞍点法计算 p 值与置信区间AI 解读

Test statistics from the weighted log-rank class are commonly used to compare treatment with control when there is right censoring. This paper uses saddlepoint methods to determine mid-p-values from the null permutation distributions of tests from the weighted log-rank class. Analytical saddlepoint computations replace the permutation simulations and provide mid-p-values that are virtually exact for all practical purposes. The speed of these saddlepoint computations makes it…