Locally optimal estimates of location
Locally weighted neural networks for an analysis of the biosensor response
This paper presents a semi-global mathematical model for an analysis of a signal of amperometric biosensors. Artificial neural networks were applied to an analysis of the biosensor response to multi-component mixtures. A large amount of the learning and test data was synthesized using computer simulation of the biosensor response. The biosensor signal was analyzed with respect to the concentration of each component of the mixture. The paradigm of locally weighted linear regression was used for retraining...
Logarithmic information of degree linked with an extension of Fisher’s information
Logically orientated cluster analysis
Logistic discrimination with many variables.
Log-periodogram regression in asymmetric long memory
The long memory property of a time series has long been studied and several estimates of the memory or persistence parameter at zero frequency, where the spectral density function is symmetric, are now available. Perhaps the most popular is the log periodogram regression introduced by Geweke and Porter–Hudak [gewe]. In this paper we analyse the asymptotic properties of this estimate in the seasonal or cyclical long memory case allowing for asymmetric spectral poles or zeros. Consistency and asymptotic...
Loi de Pareto ou loi log-normale : un choix difficile
Lois asymptotiques des tests et estimateurs de rupture dans un modèle statistique classique
Lois de von Mises et lois liées
Lois empiriques et distance de Prokhorov
Lois limites du Bootstrap de certaines fonctionnelles
Lois limites et efficacité asymptotique des tests hilbertiens de dimension finie sous des hypothèses adjacentes
Long memory properties and covariance structure of the EGARCH model
The EGARCH model of Nelson [29] is one of the most successful ARCH models which may exhibit characteristic asymmetries of financial time series, as well as long memory. The paper studies the covariance structure and dependence properties of the EGARCH and some related stochastic volatility models. We show that the large time behavior of the covariance of powers of the (observed) ARCH process is determined by the behavior of the covariance of the (linear) log-volatility process; in particular, a...
Long memory properties and covariance structure of the EGARCH model
The EGARCH model of Nelson [29] is one of the most successful ARCH models which may exhibit characteristic asymmetries of financial time series, as well as long memory. The paper studies the covariance structure and dependence properties of the EGARCH and some related stochastic volatility models. We show that the large time behavior of the covariance of powers of the (observed) ARCH process is determined by the behavior of the covariance of the (linear) log-volatility process; in particular,...
Long memory time series models
Longitudinal K-sets analysis using a dummy time variable.
Longitudinal K-sets analysis using lagged variables.
We present an application of nonlinear Generalised Canonical Analysis (GCA) for analysing longitudinal data. The application uses lagged versions of variables to accomodate the time-dependence in the measurements. The usefulness of the proposed method is illustrated in an example from developmental psychology, in which we explore the relationship between mother and child dyadic interaction during the first six months after birth, demonstrating how child behaviour can elicit mother behaviour. We...
Long-run availability of a priority system: a numerical approach.
Loss Functions and Admissible Estimators in Survey Sampling.
Loss protection in pairs trading through minimum profit bounds: A cointegration approach.