摘要:

AbstractThree regression models for ordinal data, those of Fienberg, McCullagh, and Anderson, are applied to an analysis of kidney function among transplant recipients. The conclusions arising from each model are presented and contrasted.

ISSN:0319-5724    

DOI:10.2307/3314931

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractThe following life‐testing situation is considered. At some time in the distant past,nobjects, from a population with life distributionF, were put in use; whenever an object failed, it was promptly replaced. At some time τ, long after the start of the process, a statistician starts observing thenobjects in use at that time; he knows the age of each of thosenobjects, and observes each of them for a fixed length of time≪ ∞, or until failure, whichever occurs first. In the case whereTis finite, some of the observations may be censored; in the case whereT=∞, there is no censoring. The total life of an object in use at time ∞ is a length‐biased observation fromF. A nonparametric estimator of the (cumulative) hazard function is proposed, and is used to construct an estimator ofFwhich is of the product‐limit type. Strong uniform consistency results (forn→ ∞) are obtained. An “Aalen‐Johansen” identity, satisfied by any pair of life distributions and their (cumulative) hazard functions, is used in obtaining rat

ISSN:0319-5724    

DOI:10.2307/3314932

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractWe consider the problem of comparing and testing order relations between percentile residual life functions. We introduce R‐R plots and processes and develop a general approach for this proble

ISSN:0319-5724    

DOI:10.2307/3314933

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractLet θ be a nonlinear function of the regression parameters and θ be its estimator based on the least‐squares method. This paper studies the bootstrap estimators of the variance and bias of θ. The bootstrap estimators are shown to be consistent and asymptotically unbiased under some conditions. Asymptotic orders of the mean squared errors of the bootstrap estimators are also obtained. The bootstrap and the classical linearization method are compared in a simulation study. Discussions about when to use the bootstrap are g

ISSN:0319-5724    

DOI:10.2307/3314934

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractA sample (X1…,Xn) is drawn from a population of sizeN. Karlin (1974) conjectured that for any function ϕ in a certain class of real‐valued functions on the sample space, ϕ is at least as large for sampling with replacement as for any other random replacement sampling plan. This conjecture is proved under the assumption

ISSN:0319-5724    

DOI:10.2307/3314935

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractThis article presents laws of large numbers for random elements ofD(IR). The proofs bring forth the similarities between processes restricted to compact sets ofD(IR) and processes with increasing trajectories. The results appear to generalize existing results and cover the independent identically distributed case studied by Ranga Rao.

ISSN:0319-5724    

DOI:10.2307/3314936

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractRecursive estimates fnr(x)of the rth derivative fr(x)(r=0,1)of the univariate probability densityf(x)for strictly stationary processes {Xj,} are considered. The asymptotic variance‐covariance of fnr(x)is established for stationary triangular arrays of random variables satisfying various asymptotic independence‐uncorrelatedness conditi

ISSN:0319-5724    

DOI:10.2307/3314937

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractA general procedure for obtaining matrix derivatives of functions of nonlinear patterned matrices is proposed. The method is extended to obtain the Jacobians of patterned matrix transformations. Nel (1980) and Wiens (1985) consider the linear patterned cases. The procedure proposed here takes care of these cases as well.

ISSN:0319-5724    

DOI:10.2307/3314938

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY

摘要:

AbstractLetX=(x)ij=(111, …, X,)T, i = l, …n, be annX random matrix having multivariate symmetrical distributions with parameters μ, Σ. The p‐variate normal with mean μ and covariance matrix is a member of this family. Let be the squared multiple correlation coefficient between the first and the succeeding p1components, and let p2= + be the squared multiple correlation coefficient between the first and the remaining p1+ p2=p – 1 components of the p‐variate normal vector. We shall consider here three testing problems for multivariate symmetrical distributions. They are (A) to test p2=0 against; (B) to test against =0, 0; (C) to test against p2=0, We have shown here that for problem (A) the uniformly most powerful invariant (UMPI) and locally minimax test for the multivariate normal is UMPI and is locally minimax as p20 for multivariate symmetrical distributions. For problem (B) the UMPI and locally minimax test is UMPI and locally minimax as for multivariate symmetrical distributions. For problem (C) the locally best invariant (LBI) and locally minimax test for the multivariate normal is also LBI and is locally minimax as for multivariate symmetrical d

ISSN:0319-5724    

DOI:10.2307/3314939

出版商:Wiley‐Blackwell    

年代:1988

数据来源: WILEY