Semiparametric efficiency, distribution-freeness and invariance.
By Marc Hallin, B. Werker. 2003
94 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/ca6349b668fe61495666bc87d0b831f690efee38
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Davy Paindaveine
- Thomas Verdebout
- Juan Antonio Cuesta-Albertos
- Carlos Matrán
- Marc Hallin
- Zudi Lu
- Peter M. Robinson
In Statistics and Probability
- Thomas Verdebout
- Marc Hallin
- Davy Paindaveine
- Eustasio del Barrio
- Juan Antonio Cuesta-Albertos
- Carlos Matrán
- Fang Han
- Hannu Oja
Citations in the corpus
- OPTIMAL RANK-BASED TESTING FOR PRINCIPAL COMPONENTS (2010, methodology): “This semiparametric model enjoys the double structure considered in Hallin and Werker (2003), which allows for efficient rank-based inference: the fixed-f1 subexperiments, as shown in Proposition 3.1 are ULAN, while the fixed-(θ , d ◦ vec( V), β) subexperiments [equivalently, the fixed-(θ ,V)…”
- Rank-based optimal tests of the adequacy of an elliptic VARMA model (2004, methodology): “…systematically explored, with a series of papers by Hallin, Ingenbleek and Puri (1985), Hallin and Mélard (1988) and Hallin and Puri (1988, 1991, 1994) on rank and signed rank methods for autoregressive-moving average (ARMA) and a few other [see, e.g., Hallin and Werker (2003)] time series models.”
- A canonical definition of shape (2008, unknown): “…properties of the families PnS;ϑS = {P n ϑS ,g1 : g1 ∈ F} (see, for S(Σ) = Σ11, Section 4.1 in Hallin and Paindaveine 2006a) and a general result by Hallin and Werker (2003), shows that the (semiparametrically) optimal performance (at PnϑS ,f1), when performing inference on shape in PnS =…”
- Affine-invariant aligned rank tests for the multivariate general linear model with VARMA errors (2005, background): “In such a situation, it has been shown in Hallin and Werker (2003) that, under quite general assumptions, conditioning on residual ranks leads to semiparametrically efficient—hence, in adaptive models, parametrically efficient—inference methods.”
- SEMIPARAMETRICALLY EFFICIENT RANK-BASED INFERENCE FOR SHAPE II. OPTIMAL R-ESTIMATION OF SHAPE (2006, unknown): “A general result by Hallin and Werker [17] suggests that, in case”
- SEMIPARAMETRICALLY EFFICIENT RANK-BASED INFERENCE FOR SHAPE I. OPTIMAL RANK-BASED TESTS FOR SPHERICITY (2006, background): “[20] Hallin, M. and Werker, B. J. M. (2003).”
- Distribution and quantile functions, ranks and signs in dimension d: A measure transportation approach (2021, background): “This can be interpreted as a finite-sample form of semiparametric efficiency5 In the same vein, it also has been shown (Hallin and Werker 2003) that, under appropriate regularity conditions, univariate ranks preserve semiparametric efficiency in models where that concept makes sense: (HW)…”