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排序方式: 共有238条查询结果,搜索用时 15 毫秒
131.
《Journal of computational and graphical statistics》2013,22(2):363-377
This article proposes simple estimation methods dedicated to a semiparametric family of bivariate copulas. These copulas can be simply estimated through the estimation of their univariate generating function. We use this result to estimate the associated measures of association as well as the high probability regions of the copula. These procedures are illustrated using both simulations and real data. 相似文献
132.
133.
In this paper, we provide the almost-sure convergence and the asymptotic normality of a smooth version of the Robbins–Monro algorithm for the quantile estimation. A Monte Carlo simulation study shows that our proposed method works well within the framework of a data stream. 相似文献
134.
Spline estimation of functional coefficient regression models for time series with correlated errors
In this work we focus on functional coefficient regression (FCR) models. Here we study the estimation of FCR models by splines, with autoregressive errors and show the rates of convergence of the proposed estimator. The importance of taking into account the correlation is assessed via simulation studies and multi-step ahead forecasts for a real data set. 相似文献
135.
Felix Abramovich Italia De Feis Theofanis Sapatinas 《Annals of the Institute of Statistical Mathematics》2009,61(3):691-714
We consider the problem of testing for additivity in the standard multiple nonparametric regression model. We derive optimal
(in the minimax sense) non- adaptive and adaptive hypothesis testing procedures for additivity against the composite nonparametric
alternative that the response function involves interactions of second or higher orders separated away from zero in L
2([0, 1]
d
)-norm and also possesses some smoothness properties. In order to shed some light on the theoretical results obtained, we
carry out a wide simulation study to examine the finite sample performance of the proposed hypothesis testing procedures and
compare them with a series of other tests for additivity available in the literature. 相似文献
136.
A monotone estimate of the conditional variance function in a heteroscedastic, nonparametric regression model is proposed.
The method is based on the application of a kernel density estimate to an unconstrained estimate of the variance function
and yields an estimate of the inverse variance function. The final monotone estimate of the variance function is obtained
by an inversion of this function. The method is applicable to a broad class of nonparametric estimates of the conditional
variance and particularly attractive to users of conventional kernel methods, because it does not require constrained optimization
techniques. The approach is also illustrated by means of a simulation study. 相似文献
137.
A robust local linear regression smoothing estimator for a nonparametric regression model with heavy-tailed dependent errors
is considered in this paper. Under certain regularity conditions, the weak consistency and asymptotic distribution of the
proposed estimators are obtained. If the errors are short-range dependent, then the limiting distribution of the estimator
is normal. If the data are long-range dependent, then the limiting distribution of the estimator is a stable distribution. 相似文献
138.
This paper is concerned with consistent nearest neighbor time series estimation for data generated by a Harris recurrent Markov chain on a general state space. It is shown that nearest neighbor estimation is consistent in this general time series context, using simple and weak conditions. The results proved here, establish consistency, in a unified manner, for a large variety of problems, e.g. autoregression function estimation, and, more generally, extremum estimators as well as sequential forecasting. Finally, under additional conditions, it is also shown that the estimators are asymptotically normal. 相似文献
139.
该文将Hrdle和Tsybakov的结果推广到数据来自α-混合的严平稳序列的情形,得到了估计的相合性和渐近正太性.在小样本的情形下给出了随机模拟结果,以检查所提出估计的表现. 相似文献
140.
Dennis D. Cox 《Annals of the Institute of Statistical Mathematics》1985,37(1):271-288
Summary Given a random sample of sizen from a densityf
0 on the real line satisfying certain regularity conditions, we propose a nonparametric estimator forψ
0=−f
0
′
/f0. The estimate is the minimizer of a quadratic functional of the formλJ(ψ)+∫[ψ
2−2ψ′]dFn where λ>0 is a smoothing parameter,J(·) is a roughness penalty, andF
n
is the empirical c.d.f. of the sample. A characterization of the estimate (useful for computational purposes) is given which
is related to spline functions. A more complete study of the caseJ(ψ)=∫[d
2ψ/dx2]2 is given, since it has the desirable property of giving the maximum likelihood normal estimate in the infinite smoothness
limit (λ→∞). Asymptotics under somewhat restrictive assumptions (periodicity) indicate that the estimator is asymptotically
consistent and achieves the optimal rate of convergence. This type of estimator looks promising because the minimization problem
is simple in comparison with the analogous penalized likelihood estimators.
This research was supported by the Office of Naval Research under Grant Number N00014-82-C-0062. 相似文献