排序方式: 共有69条查询结果,搜索用时 15 毫秒
1.
Charles F. Manski 《The American statistician》2019,73(1):296-304
AbstractA central objective of empirical research on treatment response is to inform treatment choice. Unfortunately, researchers commonly use concepts of statistical inference whose foundations are distant from the problem of treatment choice. It has been particularly common to use hypothesis tests to compare treatments. Wald’s development of statistical decision theory provides a coherent frequentist framework for use of sample data on treatment response to make treatment decisions. A body of recent research applies statistical decision theory to characterize uniformly satisfactory treatment choices, in the sense of maximum loss relative to optimal decisions (also known as maximum regret). This article describes the basic ideas and findings, which provide an appealing practical alternative to use of hypothesis tests. For simplicity, the article focuses on medical treatment with evidence from classical randomized clinical trials. The ideas apply generally, encompassing use of observational data and treatment choice in nonmedical contexts. 相似文献
2.
Jibo Wu 《统计学通讯:理论与方法》2017,46(6):2982-2989
This article discusses the minimax estimator in partial linear model y = Zβ + f + ε under ellipsoidal restrictions on the parameter space and quadratic loss function. The superiority of the minimax estimator over the two-step estimator is studied in the mean squared error matrix criterion. 相似文献
3.
This paper is mainly concerned with minimax estimation in the general linear regression model y=Xβ+ε under ellipsoidal restrictions on the parameter space and quadratic loss function. We confine ourselves to estimators that are linear in the response vector y . The minimax estimators of the regression coefficient β are derived under homogeneous condition and heterogeneous condition, respectively. Furthermore, these obtained estimators are the ridge-type estimators and mean dispersion error (MDE) superior to the best linear unbiased estimator b=(X′W-1X)-1X′W-1y under some conditions. 相似文献
4.
Josef Kozák 《Statistics》2013,47(3):363-371
Working with the linear regression model (1.1) and having the extraneous information (1.2) about regression coefficients the problem exists how to build estimators (1.3) with the risk (1.4) which enable to utilize the known information in order to reduce their risk as compared with the risk (1.6) of the LSE (1.5). Solution of this problem is known for the positive definite matrix T, namely in form for estimators (1.8) and (1.10).First, it is shown that the proposed estimators (2.6),(2.9) and (2.16) based on psedoinversions of the matrix L represent the solution of the problem of the positive semidefinite matrix T=L'L.Further, the problem of interpretability of estimators in the sense of the inequality (3.1) exists; it is shown that all mentioned estimators are at least partially interpretable in the sense of requirements (3.2) or (3.10). 相似文献
5.
E. Shirazi H. Doosti H.A. Niroumand N. Hosseinioun 《Journal of statistical planning and inference》2013
Here we consider wavelet-based identification and estimation of a censored nonparametric regression model via block thresholding methods and investigate their asymptotic convergence rates. We show that these estimators, based on block thresholding of empirical wavelet coefficients, achieve optimal convergence rates over a large range of Besov function classes, and in particular enjoy those rates without the extraneous logarithmic penalties that are usually suffered by term-by-term thresholding methods. This work is extension of results in Li et al. (2008). The performance of proposed estimator is investigated by a numerical study. 相似文献
6.
Minimax estimation of a binomial probability under LINEX loss function is considered. It is shown that no equalizer estimator
is available in the statistical decision problem under consideration. It is pointed out that the problem can be solved by
determining the Bayes estimator with respect to a least favorable distribution having finite support. In this situation, the
optimal estimator and the least favorable distribution can be determined only by using numerical methods. Some properties
of the minimax estimators and the corresponding least favorable prior distributions are provided depending on the parameters
of the loss function. The properties presented are exploited in computing the minimax estimators and the least favorable distributions.
The results obtained can be applied to determine minimax estimators of a cumulative distribution function and minimax estimators
of a survival function. 相似文献
7.
Roger L. Berger 《Journal of statistical planning and inference》1980,4(4):391-402
Let (X1,…,Xk) be a multinomial vector with unknown cell probabilities (p1,?,pk). A subset of the cells is to be selected in a way so that the cell associated with the smallest cell probability is included in the selected subset with a preassigned probability, P1. Suppose the loss is measured by the size of the selected subset, S. Using linear programming techniques, selection rules can be constructed which are minimax with respect to S in the class of rules which satisfy the P1-condition. In some situations, the rule constructed by this method is the rule proposed by Nagel (1970). Similar techniques also work for selection in terms of the largest cell probability. 相似文献
8.
D. Szatmari-Voicu 《统计学通讯:理论与方法》2013,42(22):4065-4077
We consider first the class of M-estimators of scale that are location-scale equivariant and Fisher consistent at the error distribution of the shrinking contamination neighborhood and derive an expression for the maximal asymptotic mean-squared-error, for a suitably regular score function, followed by a lower bound on it. We next show that the minimax asymptotic mean-squzred-error is attained at an M-estimator of scale with the truncated MLE score function which, when specialized to the Standard Normal error distribution has the form of Huber's Proposal 2. The latter minimax property is also shown to hold for α-trimmed variance as an L-estimator of scale. 相似文献
9.
Consider a positive random variable of interest Y depending on a covariate X, and a random observation time T independent of Y given X. Assume that the only knowledge available about Y is its current status at time T : δ=I{Y≤T} with I the indicator function. This paper presents a procedure to estimate the conditional cumulative distribution function F of Y given X from an independent identically distributed sample of (X,T,δ). 相似文献
10.
The paper investigates parameter estimation problems in special Markov modulated counting processes. The events occuring at any state of an underlying Markov chain can be equipped with marks performing additional information on the events. Specifying the model to the case of two-state Markov chain modulation, the so-called switched counting process, some statistical problems are studied:maximum likelihood estimators, Rao-Blackwell optimal estimators, test of equality of the counting intensities of the two states and minimax estimation procedures. Tne consideration could be applied in various practical problems, in particular, in queueing and in reliability models, for example in failure-repair processes with alternatively operating repair systems. 相似文献