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多期控制的贝叶斯启发式方法AI 解读

In multiperiod control problems, one needs to sequentially choose the value of a set of multiple input variables, xn, to keep the value of a single output variable, yn, close to a target, T. At any stage n, the selection of xn poses a difficult dilemma. On the one hand, xn has to be such that (yn(xn) - T)2 is small in expectation. On the other hand, xn has to be such that it maximizes the amount of information in yn(xn) about the model relating yn and xn, to help keep the…

切片逆回归的扩展AI 解读

Sliced inverse regression (SIR) and an associated chi-squared test for dimension have been introduced as a method for reducing the dimension of regression problems whose predictor variables are normal. In this article the assumptions on the predictor distribution, under which the chi-squared test was proved to apply, are relaxed, and the result is extended. A general weighted chi-squared test that does not require normal regressors for the dimension of a regression is given.…

不假定参数化误差分布的 Box–Cox 变换模型估计AI 解读

Box and Cox proposed a power transformation for the response variable that yields a linear regression model with normal error and constant variance. Inference procedures for the regression coefficients and transformation parameter under this model setting have been studied extensively. In this article we propose a simple semiparametric estimation method for the Box–Cox transformation model with no specific parametric assumption on the distribution of the error term. The…

随机块结构的估计与预测AI 解读

A statistical approach to a posteriori blockmodeling for digraphs and valued digraphs is proposed. The probability model assumes that the vertices of the digraph are partitioned into several unobserved (latent) classes and that the probability distribution of the relation between two vertices depends only on the classes to which they belong. A Bayesian estimator based on Gibbs sampling is proposed. The basic model is not identified, because class labels are arbitrary. The…

检验可能存在依赖的过程是否不相关AI 解读

An analysis is presented of a new testing procedure for the null hypothesis that a stochastic process is uncorrelated when the process is possibly dependent. Unlike with existing procedures, the user does not need to choose any arbitrary number to implement the proposed test. The asymptotic null distribution of the proposed test statistic is not standard, but it is tabulated by means of simulations. The test is compared with two alternative test procedures that require…

利用广义估计方程进行聚类数据的半参数回归AI 解读

We consider estimation in a semiparametric generalized linear model for clustered data using estimating equations. Our results apply to the case where the number of observations per cluster is finite, whereas the number of clusters is large. The mean of the outcome variable μ is of the form g(μ) = XTβ + θ(T), where g(·) is a link function, X and T are covariates, β is an unknown parameter vector, and θ(t) is an unknown smooth function. Kernel estimating equations proposed…

识别最大安全剂量的多重检验程序AI 解读

We consider dose response studies for safety assessment of crop protection compounds and drugs, and we offer a hypothesis testing approach for identifying the maximum dose level that is guaranteed to be safe with preassigned confidence. The focus is on step-down (SD) multiple test procedures for identifying the maximum safe dose. We propose two classes of contrasts among the dose means as test statistics for these procedures: pairwise contrasts (PC) and Helmert contrasts…

结肠远端与近端致癌物诱导 DNA 加合物水平关系的参数与非参数方法AI 解读

An important problem in studying the etiology of colon cancer is understanding the relationship between DNA adduct levels (broadly, DNA damage) in cells within colonic crypts in distal and proximal parts of the colon, following treatment with a carcinogen and different types of diet. In particular, it is important to understand whether rats who have elevated adduct levels in particular positions in distal region crypts also have elevated levels in the same positions of the…

非线性模型中的简便稳健假设检验AI 解读

We develop test statistics to test hypotheses in nonlinear weighted regression models with serial correlation or conditional heteroscedasticity of unknown form. The novel aspect is that these tests are simple and do not require the use of heteroscedasticity autocorrelationconsistent (HAC) covariance matrix estimators. This new class of tests uses stochastic transformations to eliminate nuisance parameters as a substitute for consistently estimating the nuisance parameters.…

广义线性模型的稳健推断AI 解读

By starting from a natural class of robust estimators for generalized linear models based on the notion of quasi-likelihood, we define robust deviances that can be used for stepwise model selection as in the classical framework. We derive the asymptotic distribution of tests based on robust deviances, and we investigate the stability of their asymptotic level under contamination. The binomial and Poisson models are treated in detail. Two applications to real data and a…

调查中高影响群组的降权处理AI 解读

Certain clusters may be extremely influential on survey estimates and consequently contribute disproportionately to their variance. We propose a general approach to estimation that downweights highly influential clusters, with the amount of downweighting based on M-estimation applied to the empirical influence of the clusters. The method is motivated by a problem in census coverage estimation, and we illustrate it by using data from the 1990 Post Enumeration Survey (PES). In…

含相关状态依赖噪声与滤波效应的离子通道隐马尔可夫分析AI 解读

A hidden Markov model that describes ion channel data, including correlated, state-dependent noise and filter characteristics, and a Markov chain Monte Carlo algorithm that enables Bayesian inference under this model are presented. The method provides parameter estimates and an estimate of the noiseless signal. It was tested on simulated data and applied to real recordings to estimate the model parameters. Modeling the noise and filter correctly turned out to be crucial for…

工具变量估计量精确小样本性质的进一步结果AI 解读

generous referee; remaining errors are my own. The exact finite sample distribution for the two-stage least square estimator has been derived for quite general situations (see Phillips (1983) for a survey of the literature). Unfortunately, these general expressions do not lend themselves to easy interpretations. Consequently, a number of authors have looked at special cases to illustrate some of the problems that can arise when using asymptotic distribution results for…

任何检验都可被操纵AI 解读

Abstract. A forecaster provides a probabilistic prediction regarding the following day’s state of nature. To examine the forecaster, an inspector employs calibration tests that compare the average prediction and the empirical frequency of pre-specified events. This paper shows that any mixed test can be manipulated in the sense that, independently of the state realizations, the difference between the average prediction and the past empirical frequency that corresponds to…

含线性时间趋势的自回归模型中的子抽样置信区间AI 解读

A new method is proposed for constructing confidence intervals in autoregressive models with linear time trend. Interest focuses on the sum of the autoregressive coefficients because this parameter provides a useful scalar measure of the long-run persistence properties of an economic time series. Since the type of the limiting distribution of the corresponding OLS estimator, as well as the rate of its convergence, depend in a discontinuous fashion upon whether the true…

非嵌套假设的得分检验及其离散数据模型应用AI 解读

Abstract In this paper it is shown that a convenient score test against non‐nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. This is essentially a test for the correct specification of the conditional distribution of the variable of interest. Given its characteristics, the proposed test is particularly attractive to check the distributional assumptions in models for discrete data. The usefulness of the…

跨国增长回归中的模型不确定性AI 解读

Abstract We investigate the issue of model uncertainty in cross‐country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is spread widely among many models, suggesting the superiority of BMA over choosing any single model. Out‐of‐sample predictive results support this claim. In contrast to Levine and Renelt ( 1992 ), our results broadly support the more ‘optimistic’ conclusion of Sala‐i‐Martin ( 1997b ), namely that some…

通过最大化最低 D 与 D₁ 效率构造多项式回归稳健设计AI 解读

In the common polynomial regression of degree m we determine the design which maximizes the minimum of the $D$-efficiency in the model of degree $m$ and the $D_1$-efficiencies in the models of degree $m-j,\dots, m +k$ ($j, k\ge 0$ given). The resulting designs allow an efficient estimation of the parameters in the chosen regression and have reasonable efficiencies for checking the goodness-of-fit of the assumed model of degree $m$ by testing the highest coefficients in the…

用于混合模型诊断的拟合优度检验AI 解读

A simple goodness of fit test is proposed for checking distributional assumptions involved in a mixed linear model. An estimated critical value of the test statistic is derived, and is shown to be asymptotically correct under mild conditions. As a special case,the test may be applied to linear regression models to formally check distribution of the errors. Finite sample performance of the proposed test is examined and compared with that of a previously proposed test by…

二项模型的稳健拟合AI 解读

We consider the problem of robust inference for the binomial $(m, \pi)$ model. The discreteness of the data and the fact that the parameter and sample spaces are bounded mean that standard robustness theory gives surprising results. For example, the maximum likelihood estimator (MLE) is quite robust, it cannot be improved on for $m=1$ but can be for $m>1$. We discuss four other classes of estimators: $M$-estimators, minimum disparity estimators, optimal MGP estimators, and a…

广义矩条件下计算Γ极小极大决策规则的算法AI 解读

We present an algorithm for calculating a $\Gamma$-minimax decision rule, when is given by a finite number of generalized moment conditions. Such a decision rule minimizes the maximum of the integrals of the risk function with respect to all distributions in $\Gamma$. The inner maximization problem is approximated by a sequence of linear programs. This approximation is combined with an elimination technique which quickly reduces the domain of the variables of the outer…

正交饱和设计自适应分析中的错误率控制AI 解读

Individual and simultaneous confidence intervals using the data adaptively are constructed for the effects in orthogonal saturated designs under the assumption of effect sparsity. The minimum coverage probabilities of the intervals are equal to the nominal level $1 - \alpha$.

逻辑回归检验的局部渐近最优设计AI 解读

Design measures maximizing local power of asymptotically uniformly most powerful (AUMP) tests about the value of logitP outside the observation space are characterized.

非平稳过程的窄频带分析AI 解读

The behavior of averaged periodograms and cross-periodograms of a broad class of nonstationary processes is studied. The processes include nonstationary ones that are fractional of any order, as well as asymptotically stationary fractional ones. The cross-periodogram can involve two nonstationary processes of possibly different orders, or a nonstationary and an asymptotically stationary one. The averaging takes place either over the whole frequency band, or over one that…