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primary 59 Copula 15 Asymptotic normality 14 Variable selection 14 Bootstrap 12 Order statistics 11 Consistency 10 Covariance matrix 10 Dimension reduction 10 Longitudinal data 10 Nonparametric regression 10 asymptotic normality 10 EM algorithm 9 Empirical likelihood 9 Oracle property 9 Robust estimation 9 Hypothesis testing 8 Kernel smoothing 8 Nonparametric estimation 8 Elliptical distribution 7 Elliptically contoured distribution 7 Empirical Bayes 7 High-dimensional data 7 Multivariate normal distribution 7 Sufficient dimension reduction 7 Central limit theorem 6 Linear mixed model 6 Model selection 6 Principal component analysis 6 SCAD 6 Sliced inverse regression 6 U-statistic 6 Dirichlet distribution 5 Discriminant analysis 5 Estimating equations 5 Heteroscedasticity 5 Majorization 5 Markov chain Monte Carlo 5 Maximum likelihood estimator 5 Missing at random 5
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Hall, Peter 26 Fujikoshi, Yasunori 24 Balakrishnan, N. 23 Kubokawa, Tatsuya 20 Khatri, C. G. 19 Krishnaiah, P. R. 19 Sen, Pranab Kumar 19 Takemura, Akimichi 18 Bai, Z. D. 17 Horváth, Lajos 16 Srivastava, M. S. 16 Strawderman, William E. 16 Wang, Qihua 16 Puri, Madan L. 15 Rao, C. Radhakrishna 15 Srivastava, Muni S. 15 Zhu, Lixing 15 Ghosh, Malay 13 Gupta, Arjun K. 13 Joe, Harry 13 Zhu, Li-Xing 12 Hu, Taizhong 11 Nadarajah, Saralees 11 Richards, Donald St. P. 11 Shaked, Moshe 11 Tsai, Ming-Tien 11 You, Jinhong 11 Arellano-Valle, Reinaldo B. 10 Boente, Graciela 10 Fourdrinier, Dominique 10 Genton, Marc G. 10 Lian, Heng 10 Scarsini, Marco 10 Díaz-García, José A. 9 Kariya, Takeaki 9 Mathew, Thomas 9 Peng, Liang 9 Silverstein, Jack W. 9 von Rosen, Dietrich 9 Chikuse, Yasuko 8
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Journal of Multivariate Analysis 3,562
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Showing 3,261 - 3,270 of 3,562
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A result on hypothesis testing for a multivariate normal distribution when some observations are missing
Cohen, Arthur - In: Journal of Multivariate Analysis 7 (1977) 3, pp. 454-460
Let Ui = (Xi, Yi), i = 1, 2,..., n, be a random sample from a bivariate normal distribution with mean [mu] = ([mu]x, [mu]y) and covariance matrix . Let Xi, i = n + 1,..., N represent additional independent observations on the X population. Consider the hypothesis testing problem H0 : [mu] = 0...
Persistent link: https://www.econbiz.de/10005006494
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Stochastic processes with independent increments, taking values in a Hilbert space
Spielman, Jeffrey L. - In: Journal of Multivariate Analysis 6 (1976) 3, pp. 426-446
Let be a real separable Hilbert space; let X(t), t[epsilon][0, 1], be a separable, stochastically continuous, -valued stochastic process with independent increments. Then a decomposition of X(t) into a uniformly convergent sum of independent processes is found. In this decomposition one of the...
Persistent link: https://www.econbiz.de/10005006500
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Representation of certain infinitely divisible probability measures on Banach spaces
Kumar, Arunod; Schreiber, Bertram M. - In: Journal of Multivariate Analysis 9 (1979) 2, pp. 288-303
Subclasses L0 [superset or implies] L1 [superset or implies] ... [superset or implies] L[infinity] of the class L0 of self-decomposable probability measures on a Banach space are defined by means of certain stability conditions. Each of these classes is closed under translation, convolution and...
Persistent link: https://www.econbiz.de/10005006502
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On deviations between empirical and quantile processes for mixing random variables
Babu, Gutti Jogesh; Singh, Kesar - In: Journal of Multivariate Analysis 8 (1978) 4, pp. 532-549
Let {Xn} be a strictly stationary [phi]-mixing process with [Sigma]j=1[infinity] [phi]1/2(j) [infinity]. It is shown in the paper that if X1 is uniformly distributed on the unit interval, then, for any t [set membership, variant] [0, 1], Fn-1(t) - t + Fn(t) - t = O(n-3/4(log log n)3/4) a.s. and...
Persistent link: https://www.econbiz.de/10005006508
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Asymptotic expansions for the distributions of functions of a correlation matrix
Konishi, Sadanori - In: Journal of Multivariate Analysis 9 (1979) 2, pp. 259-266
This paper deals with asymptotic expansions for the non-null distributions of certain test statistics concerning a correlation matrix in a multivariate normal distribution. For this purpose an asymptotic expansion is given for the distribution of a function of the sample correlation matrix. As...
Persistent link: https://www.econbiz.de/10005006513
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Equivalence of measures for some class of Gaussian random fields
Inoue, K. - In: Journal of Multivariate Analysis 6 (1976) 2, pp. 295-308
We consider two Gaussian measures P1 and P2 on (C(G), ) with zero expectations and covariance functions R1(x, y) and R2(x, y) respectively, where R[nu](x, y) is the Green's function of the Dirichlet problem for some uniformly strongly elliptic differential operator A([nu]) of order 2m, m = [d/2]...
Persistent link: https://www.econbiz.de/10005006542
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Exponential inequalities for sums of random vectors
Yurinskii, V. V. - In: Journal of Multivariate Analysis 6 (1976) 4, pp. 473-499
This paper presents some generalizations of S. N. Bernstein's exponential bounds on probabilities of large deviations to the vector case. Inequalities for probabilities of large deviations of sums of independent random vectors are derived under a Cramér's type restriction on the rate of growth...
Persistent link: https://www.econbiz.de/10005006544
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Martingales on von Neumann algebras
Cuculescu, I. - In: Journal of Multivariate Analysis 1 (1971) 1, pp. 17-27
We consider L1 bounded martingales on a von Neumann algebra with respect to a given ascending sequence of von Neumann subalgebras as functionals on the C*-algebra which is the uniform closure of the union of those subalgebras. We define the singular martingales, prove the "Krickeberg...
Persistent link: https://www.econbiz.de/10005006549
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Multivariate distributions having Weibull properties
Lee, Larry - In: Journal of Multivariate Analysis 9 (1979) 2, pp. 267-277
Random variables X1 ,..., Xn are said to have a joint distribution with Weibull minimums after arbitrary scaling if mini(aiXi) has a one dimensional Weibull distribution for arbitrary constants ai 0, I = 1,..., n. Some properties of this class are demonstrated, and some examples are given which...
Persistent link: https://www.econbiz.de/10005006550
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Optimum designs when the observations are second-order processes
Spruill, Carl; Studden, W. J. - In: Journal of Multivariate Analysis 8 (1978) 2, pp. 153-172
Let the process {Y(x,t) : t [epsilon] T} be observable for each x in some compact set X. Assume that Y(x, t) = [theta]0f0(x)(t) + ... + [theta]kfk(x)(t) + N(t) where fi are continuous functions from X into the reproducing kernel Hilbert space H of the mean zero random process N. The optimum...
Persistent link: https://www.econbiz.de/10005006559
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