Results 111 to 120 of about 29,960 (243)

Specification Tests for Jump‐Diffusion Models Based on the Characteristic Function

International Statistical Review, EarlyView.
Summary Goodness‐of‐fit tests are suggested for several popular jump‐diffusion processes. The suggested test statistics utilise the marginal characteristic function of the model and its L2‐type discrepancy from an empirical counterpart. Model parameters are estimated either by minimising the aforementioned L2‐type discrepancy or by maximum likelihood ...
Gerrit Lodewicus Grobler, Denis Belomestny, Simos George Meintanis, Emanuele Taufer   +3 more
wiley   +1 more source

On a Generalized Alpha Skew Laplace Distribution: Properties and Applications

Austrian Journal of Statistics
This study introduces a novel extension of the alpha skew Laplace distribution  (Harandi and Alamatsaz 2013), designed to model datasets with both unimodal and bimodal characteristics effectively.
Jondeep Das, Partha Jyoti Hazarika, Dimpal Pathak, Piotr Sulewski   +3 more
doaj   +1 more source

Generalized Autoregressive Score asymmetric Laplace Distribution and Extreme Downward Risk Prediction

, 2020
Due to the skessed distribution, high peak and thick tail and asymmetry of financial return data, it is difficult to describe the traditional distribution. In recent years, generalized autoregressive score (GAS) has been used in many fields and achieved good results.
openaire   +2 more sources

Bias Adjustment for Mean Squared Error Estimation in M‐Quantile Models for Small Area Estimation

International Statistical Review, EarlyView.
Summary M‐quantile (MQ) regression provides a robust and flexible alternative to mixed models for small area estimation. However, several theoretical aspects remain underexplored. In this paper, a parametric bootstrap method is proposed to approximate the distributions of area‐specific MQ coefficients and applied to adjust the bias in the mean squared ...
María Bugallo, Domingo Morales, Nicola Salvati, Francesco Schirripa Spagnolo   +3 more
wiley   +1 more source

A latent class based imputation method under Bayesian quantile regression framework using asymmetric Laplace distribution for longitudinal medication usage data with intermittent missing values. [PDF]

J Biopharm Stat, 2020
Lee M, Rahbar MH, Gensler LS, Brown M, Weisman M, Reveille JD.   +5 more
europepmc   +1 more source

Asymmetric Laplace distribution regression model for fitting heterogeneous longitudinal response

The systematic collection of longitudinal data is very common in practice, making mixed models widely used. Most developments around these models focus on modeling the mean trajectory of repeated measurements, typically under the assumption of homoskedasticity.
Barbieri, Antoine, Alcaraz, Angelo, Abed, Mouna, de Courson, Hugues, Jacqmin-Gadda, Hélène   +4 more
openaire   +2 more sources

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

Journal of Economic Surveys, EarlyView.
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte, Konstantinos N. Konstantakis, Dimitris Konstantios, Panayotis G. Michaelides, Arsenios‐Georgios N. Prelorentzos   +4 more
wiley   +1 more source

Asymmetric Uniform-Laplace distribution: Properties and Applications [PDF]

Journal of the Iranian Statistical Society, 2018
Fatemeh Arezoomand, Masoud Yarmohammadi, Rahim Mahmoudvand   +2 more
openaire   +1 more source

Robust CDF‐Filtering of a Location Parameter

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania, Andrew C. Harvey, Alessandra Luati   +2 more
wiley   +1 more source

Model and distribution uncertainty in multivariate GARCH estimation: a Monte Carlo analysis [PDF]

Multivariate GARCH models are in principle able to accommodate the features of the dynamic conditional correlations processes, although with the drawback, when the number of financial returns series considered increases, that the parameterizations entail
Rossi, Eduardo, Spazzini, Filippo
core   +1 more source