AbstractAn asymptotic distribution theory is developed for a general class of signed-rank serial statistics, and is then used to derive asymptotically locally optimal tests (in the maximin sense) for testing an ARMA model against other ARMA models. Special cases yield Fisher-Yates, van der Waerden, and Wilcoxon type tests. The asymptotic relative efficiencies of the proposed procedures with respect to each other, and with respect to their normal theory counterparts, are provided
AbstractWe develop optimal rank-based procedures for testing affine-invariant linear hypotheses on t...
Asymptotic linearity plays a key role in estimation and testing in the presence of nuisance paramete...
This paper develops an approach to rank testing that nests all existing rank tests and simplifies th...
AbstractAn asymptotic distribution theory is developed for a general class of signed-rank serial sta...
AbstractLinear models in which the unobserved error constitutes a realization of some stationary ARM...
AbstractLinear models in which the unobserved error constitutes a realization of some stationary ARM...
Linear models in which the unobserved error constitutes a realization of some stationary ARMA proces...
Optimal rank-based procedures were derived in Hallin, Ingenbleek, and Puri (1985, 1987) and Hallin a...
AbstractA class of linear serial multirank statistics is introduced for the problem of testing the n...
Abstract. The classical theory of rank-based inference is essentially limited to univariate linear m...
AbstractA class of linear serial multirank statistics is introduced for the problem of testing the n...
The classical theory of rank-based inference is entirely based either on ordinary ranks, which do n...
Abstract. In this paper we develop an asymptotic theory for estima-tion based on signed ranks in the...
The classical theory of rank-based inference is entirely based either on ordinary ranks, which do no...
Optimal (signed and unsigned) rank-based procedures are derived for the problem of testing autoregre...
AbstractWe develop optimal rank-based procedures for testing affine-invariant linear hypotheses on t...
Asymptotic linearity plays a key role in estimation and testing in the presence of nuisance paramete...
This paper develops an approach to rank testing that nests all existing rank tests and simplifies th...
AbstractAn asymptotic distribution theory is developed for a general class of signed-rank serial sta...
AbstractLinear models in which the unobserved error constitutes a realization of some stationary ARM...
AbstractLinear models in which the unobserved error constitutes a realization of some stationary ARM...
Linear models in which the unobserved error constitutes a realization of some stationary ARMA proces...
Optimal rank-based procedures were derived in Hallin, Ingenbleek, and Puri (1985, 1987) and Hallin a...
AbstractA class of linear serial multirank statistics is introduced for the problem of testing the n...
Abstract. The classical theory of rank-based inference is essentially limited to univariate linear m...
AbstractA class of linear serial multirank statistics is introduced for the problem of testing the n...
The classical theory of rank-based inference is entirely based either on ordinary ranks, which do n...
Abstract. In this paper we develop an asymptotic theory for estima-tion based on signed ranks in the...
The classical theory of rank-based inference is entirely based either on ordinary ranks, which do no...
Optimal (signed and unsigned) rank-based procedures are derived for the problem of testing autoregre...
AbstractWe develop optimal rank-based procedures for testing affine-invariant linear hypotheses on t...
Asymptotic linearity plays a key role in estimation and testing in the presence of nuisance paramete...
This paper develops an approach to rank testing that nests all existing rank tests and simplifies th...