Relevant bibliographies by topics / Locally asymptotically normality

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Reports

Academic literature on the topic 'Locally asymptotically normality'

Author: Grafiati
Published: 8 June 2024
Last updated: 31 July 2025

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Journal articles on the topic "Locally asymptotically normality"

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Boswijk, H. Peter. "MIXED NORMALITY AND ANCILLARITY IN I(2) SYSTEMS." Econometric Theory 16, no. 6 (2000): 878–904. http://dx.doi.org/10.1017/s0266466600166046.

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This paper studies asymptotic likelihood inference on cointegration parameters in systems integrated of order two. We start with so-called triangular systems and then extend the analysis to vector autoregressions. We show that even when all unit root restrictions have been imposed, the asymptotic observed information is not (locally) ancillary, which implies that the log-likelihood ratio is not locally asymptotically mixed normal. The results are applied to inference on polynomial cointegration. Some similarities and differences with I(1) systems are also discussed.
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Bezziche, Nesrine, and Mouna Merzougui. "Optimal Tests for Distinguishing PAR Models from PSETAR Models." Statistics, Optimization & Information Computing 13, no. 5 (2025): 1868–79. https://doi.org/10.19139/soic-2310-5070-2240.

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This paper aims to detect nonlinearity in periodic autoregressive models. We introduce parametric and semiparametric local asymptotic optimal tests designed for distinguishing a periodic autoregressive model from a periodic self-exciting threshold autoregressive (SETAR) model. Leveraging the Local Asymptotic Normality (LAN) property specific to periodic SETAR models, we devise a parametric test that is locally asymptotically most stringent. Additionally, the utilization of kernel estimation for the density function allows the construction of an adaptive test for enhanced flexibility and accura
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Bentarzi, Mohamed, and Marc Hallin. "Locally Optimal Tests against Periodic Autoregression: Parametric and Nonparametric Approaches." Econometric Theory 12, no. 1 (1996): 88–112. http://dx.doi.org/10.1017/s0266466600006459.

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Locally asymptotically optimal tests are derived for the null hypothesis of traditional AR dependence, with unspecified AR coefficients and unspecified innovation densities, against an alternative of periodically correlated AR dependence. Parametric and nonparametric rank-based versions are proposed. Local powers and asymptotic relative efficiencies (with respect, e.g., to the corresponding Gaussian Lagrange multiplier tests proposed in Ghysels and Hall [1992, “Lagrange Multiplier Tests for Periodic Structures,” unpublished manuscript, CRDE, Montreal] and Liitkepohl [1991, Introduction to Mult
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Saidi, Abdessamad, and Roch Roy. "ROBUST OPTIMAL TESTS FOR CAUSALITY IN MULTIVARIATE TIME SERIES." Econometric Theory 24, no. 4 (2008): 948–87. http://dx.doi.org/10.1017/s0266466608080377.

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Here, we derive optimal rank-based tests for noncausality in the sense of Granger between two multivariate time series. Assuming that the global process admits a joint stationary vector autoregressive (VAR) representation with an elliptically symmetric innovation density, both no feedback and one direction causality hypotheses are tested. Using the characterization of noncausality in the VAR context, the local asymptotic normality (LAN) theory described in Le Cam (1986, Asymptotic Methods in Statistical Decision Theory) allows for constructing locally and asymptotically optimal tests for the n
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Lmakri, Aziz, Abdelhadi Akharif, and Amal Mellouk. "Optimal Detection of Bilinear Dependence in Short Panels of Regression Data." Revista Colombiana de Estadística 43, no. 2 (2020): 143–71. http://dx.doi.org/10.15446/rce.v43n2.83044.

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In this paper, we propose parametric and nonparametric locally andasymptotically optimal tests for regression models with superdiagonal bilinear time series errors in short panel data (large n, small T). We establish a local asymptotic normality property– with respect to intercept μ, regression coefficient β, the scale parameter σ of the error, and the parameter b of panel superdiagonal bilinear model (which is the parameter of interest)– for a given density f1 of the error terms. Rank-based versions of optimal parametric tests are provided. This result, which allows, by Hájek’s representation
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Dissertations / Theses on the topic "Locally asymptotically normality"

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Salman, Youssef. "Testing a class of time-varying coefficients CHARN models with application to change-point study." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0170.

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Dans cette thèse, nous étudions un test du rapport de vraisemblance pour détecter les ruptures faibles dans la moyenne conditionnelle d'une classe de modèles CHARN à coefficients dépendants du temps. Nous établissons la structure de normalité asymptotique locale (LAN) de la famille de vraisemblances étudiées. Nous montrons l'optimalité asymptotique du test et donnons une expression explicite de sa puissance locale en fonction des potentiels points de rupture et des amplitudes des ruptures. Nous décrivons des stratégies de détection des ruptures et d'estimation de leurs localisations. Les estim
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Books on the topic "Locally asymptotically normality"

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Cheng, Russell. Standard Asymptotic Theory. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0003.

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This book relies on maximum likelihood (ML) estimation of parameters. Asymptotic theory assumes regularity conditions hold when the ML estimator is consistent. Typically an additional third derivative condition is assumed to ensure that the ML estimator is also asymptotically normally distributed. Standard asymptotic results that then hold are summarized in this chapter; for example, the asymptotic variance of the ML estimator is then given by the Fisher information formula, and the log-likelihood ratio, the Wald and the score statistics for testing the statistical significance of parameter es
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Book chapters on the topic "Locally asymptotically normality"

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Tarima, Sergey, and Nancy Flournoy. "Choosing Interim Sample Sizes in Group Sequential Designs." In German Medical Data Sciences: Bringing Data to Life. IOS Press, 2021. http://dx.doi.org/10.3233/shti210043.

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This manuscript investigates sample sizes for interim analyses in group sequential designs. Traditional group sequential designs (GSD) rely on “information fraction” arguments to define the interim sample sizes. Then, interim maximum likelihood estimators (MLEs) are used to decide whether to stop early or continue the data collection until the next interim analysis. The possibility of early stopping changes the distribution of interim and final MLEs: possible interim decisions on trial stopping excludes some sample space elements. At each interim analysis the distribution of an interim MLE is
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Reports on the topic "Locally asymptotically normality"

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Amengual, Dante, Xinyue Bei, Marine Carrasco, and Enrique Sentana. Score-type tests for normal mixtures. CIRANO, 2023. http://dx.doi.org/10.54932/uxsg1990.

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Testing normality against discrete normal mixtures is complex because some parameters turn increasingly underidentified along alternative ways of approaching the null, others are inequality constrained, and several higher-order derivatives become identically 0. These problems make the maximum of the alternative model log-likelihood function numerically unreliable. We propose score-type tests asymptotically equivalent to the likelihood ratio as the largest of two simple intuitive statistics that only require estimation under the null. One novelty of our approach is that we treat symmetrically b
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