共查询到20条相似文献,搜索用时 31 毫秒
1.
Let X(1,n,m1,k),X(2,n,m2,k),…,X(n,n,m,k) be n generalized order statistics from a continuous distribution F which is strictly increasing over (a,b),−∞≤a<b≤∞, the support of F. Let g be an absolutely continuous and monotonically increasing function in (a,b) with finite g(a+),g(b−) and E(g(X)). Then for some positive integer s,1<s≤n, we give characterization of distributions by means of 相似文献
2.
We consider the situation where one wants to maximise a functionf(θ,x) with respect tox, with θ unknown and estimated from observationsy
k
. This may correspond to the case of a regression model, where one observesy
k
=f(θ,x
k
)+ε
k
, with ε
k
some random error, or to the Bernoulli case wherey
k
∈{0, 1}, with Pr[y
k
=1|θ,x
k
|=f(θ,x
k
). Special attention is given to sequences given by
, with
an estimated value of θ obtained from (x1, y1),...,(x
k
,y
k
) andd
k
(x) a penalty for poor estimation. Approximately optimal rules are suggested in the linear regression case with a finite horizon,
where one wants to maximize ∑
i=1
N
w
i
f(θ, x
i
) with {w
i
} a weighting sequence. Various examples are presented, with a comparison with a Polya urn design and an up-and-down method
for a binary response problem. 相似文献
3.
The (n,f,k(i,j)):F(? n,f,k(i,j)?:F) system consists of n components ordered in a line or circle, while the system fails if, and only if, there exist at least f failed components OR (AND) at least k consecutive failed components among components i,i + 1,…,j ? 1,j. In this article, we present the system reliability formulae for these systems with product of matrices by means of a two-stage finite Markov chain imbedding approach, a technique first used by Cui et al. (2002). In addition, their dual systems, denoted by (n,f,k(i,j)):G and ? n,f,k(i,j)?:G, are also introduced. Two numerical examples are given to illustrate the results. 相似文献
4.
K. K. Kamalja 《统计学通讯:理论与方法》2014,43(10-12):2406-2418
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Davinder Kumar Garg 《统计学通讯:理论与方法》2013,42(19):3485-3491
A New Modified Latin square [NML i (m)] association scheme with i constraints for v = m 2 treatments was introduced by Garg (2008). In this article, a new association scheme known as Pseudo New Modified Latin square [Pseudo NML m (m)] type association scheme is defined. The parameters of Pseudo NML m (m) association scheme turned out to be parameters of NML i (m) association scheme by taking i = m in NML i (m) association scheme. The Pseudo NML m (m) association scheme will be the usual NML m (m) association scheme when m is a prime or a prime power. The PBIB designs following Pseudo NML m (m) association scheme will be called the Pseudo NML m (m) type PBIB designs. Analysis of Pseudo NML m (m) designs along with a construction method of these designs is also given in this article. 相似文献
8.
Y. H. Wang 《Revue canadienne de statistique》1986,14(1):69-74
Let X and Y be two arbitrary k-dimensional discrete random vectors, for k ≥ 1. We prove that there exists a coupling method which minimizes P( X ≠ Y ). This result is used to find the least upper bound for the metric d( X, Y ) = supA|P( X ∈ A ) ? P( Y ∈ A )| and to derive the inequality d(Σ X i, Σ Y i) ≤ Σd( X i, Y i). We thus obtain a unified method to measure the disparity between the distributions of sums of independent random vectors. Several examples are given. 相似文献
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Sergio Alvarez-Andrade 《统计学通讯:理论与方法》2013,42(5):1044-1052
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Czesław Ste¸pniak 《统计学通讯:理论与方法》2013,42(13):2405-2412
Canonical form plays a similar role in linear models to spectral decomposition in matrix analysis. Let X = (X 1,…, X n )′ be a random vector with expectation Aβ and the variance–covariance matrix σV, where V is positive definite and let rank(A) = r. Then there exists a nonsingular linear transformation from X to T = (T 1,…, T n )′, such that ET i = η i , for i = 1,…, r and zero for i > r, while cov(T i , T j ) = δ ij σ. This canonical form, introduced by Ko?odziejczyk (1935), was used, among others, by Scheffé (1959) and by Lehmann (1959, 1986). This technique is extended here for arbitrary (possibly singular) V and for simultaneous canonization of two models of this type. 相似文献
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Given an orthogonal modelan L modelis obtained, and the only restriction is the linear independency of the column vectors of matrix L. Special cases of the L models correspond to blockwise diagonal matrices L = D(L 1, . . . , L c ). In multiple regression designs this matrix will be of the formwith \({\check{{\bf X}}_j, j=1,\ldots,c}\) the model matrices of the individual regressions, while the original model will have fixed effects. In this way, we overcome the usual restriction of requiring all regressions to have the same model matrix.
相似文献
${{\bf \lambda}}=\sum_{i=1}^m{{{\bf X}}_i}{\boldsymbol{\alpha}}_i$
${{\bf y}}={\bf L}\left(\sum_{i=1}^m{{{\bf X}}_i}{\boldsymbol{\alpha}}_i\right)+{\bf e}$
${\bf L}={\bf D}(\check{{\bf X}}_1,\ldots,\check{{\bf X}}_{c})$
14.
Let Π1,…,Πk be k populations with Πi being Pareto with unknown scale parameter αi and known shape parameter βi;i=1,…,k. Suppose independent random samples (Xi1,…,Xin), i=1,…,k of equal size are drawn from each of k populations and let Xi denote the smallest observation of the ith sample. The population corresponding to the largest Xi is selected. We consider the problem of estimating the scale parameter of the selected population and obtain the uniformly minimum variance unbiased estimator (UMVUE) when the shape parameters are assumed to be equal. An admissible class of linear estimators is derived. Further, a general inadmissibility result for the scale equivariant estimators is proved. 相似文献
15.
Shuenn-Ren Cheng 《统计学通讯:理论与方法》2013,42(10):1553-1560
We observe X 1,…,X k , where X i has density f(x,θ i ) possessing monotone likelihood ratio. The best population corresponds to the largest θ i . We select the population corresponding to the largest X i . The goal is to attach the best possible p-value to the inference: the selected population has the uniquely largest θ i . Gutmann and Maymin (1987) considered the location parameter case and derived the supremum of the error probability by conditioning on S, the index of the largest X i . Using this conditioning approach, Kannan and Panchapakesan (2009) considered the problem for the gamma family. We consider here a unified approach to both the location and scale parameter cases, and obtain the supremum of the error probability without using conditioning. 相似文献
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Lanh Tat Tran 《Revue canadienne de statistique》1991,19(4):371-387
Let X1 be a strictly stationary multiple time series with values in Rd and with a common density f. Let X1,.,.,Xn, be n consecutive observations of X1. Let k = kn, be a sequence of positive integers, and let Hni be the distance from Xi to its kth nearest neighbour among Xj, j i. The multivariate variable-kernel estimate fn, of f is defined by where K is a given density. The complete convergence of fn, to f on compact sets is established for time series satisfying a dependence condition (referred to as the strong mixing condition in the locally transitive sense) weaker than the strong mixing condition. Appropriate choices of k are explicitly given. The results apply to autoregressive processes and bilinear time-series models. 相似文献
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