Search results for "STATISTICS & PROBABILITY"

Nonlinear GARCH models for highly persistent volatility

2005

In this paper we study new nonlinear GARCH models mainly designed for time series with highly persistent volatility. For such series, conventional GARCH models have often proved unsatisfactory because they tend to exaggerate volatility persistence and exhibit poor forecasting ability. Our main emphasis is on models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable corresponds to the idea that high persistence in conditional variance is related to relatively infrequent changes in regime. U sing the theory of Markov chains w…

Sampling properties of the Bayesian posterior mean with an application to WALS estimation

2022

Many statistical and econometric learning methods rely on Bayesian ideas, often applied or reinterpreted in a frequentist setting. Two leading examples are shrinkage estimators and model averaging estimators, such as weighted-average least squares (WALS). In many instances, the accuracy of these learning methods in repeated samples is assessed using the variance of the posterior distribution of the parameters of interest given the data. This may be permissible when the sample size is large because, under the conditions of the Bernstein--von Mises theorem, the posterior variance agrees asymptotically with the frequentist variance. In finite samples, however, things are less clear. In this pa…

DETECTING VOLCANIC ERUPTIONS IN TEMPERATURE RECONSTRUCTIONS BY DESIGNED BREAK-INDICATOR SATURATION

2016

We present a methodology for detecting breaks at any point in time-series regression models using an indicator saturation approach, applied here to modelling climate change. Building on recent developments in econometric model selection for more variables than observations, we saturate a regression model with a full set of designed break functions. By selecting over these break functions using an extended general-to-specific algorithm, we obtain unbiased estimates of the break date and magnitude. Monte Carlo simulations confirm the approximate properties of the approach. We assess the methodology by detecting volcanic eruptions in a time series of Northern Hemisphere mean temperature spanni…

Efficiency of French privatizations: a dynamic vision

2004

The program of French privatizations is one of the principal worldwide programs as for the volume of the equity issues. A reading of the process of privatization through the corporate governance theory resulted in working out a model making it possible to take into account, on the one hand, the time dimension of the process of privatization, on the other hand, the contextual, organizational, governance and strategic variables which influence this process. After having replicated a certain number of traditional tests, we carried out a test of this model on a sample of 19 French privatized firms and on a seven years horizon, which made it possible to obtain the following conclusions. The favo…

Management of Distribution Risks and Digital Transformation of Insurance Distribution—A Regulatory Gap in the IDD

2021

The Insurance Distribution Directive (IDD) aims to regulate insurance distribution in the EU regardless of distribution channels and means. Although new technologies affect insurance distribution, the IDD does not explicitly regulate this digital transformation. Insurers and intermediaries must comply with detailed business conduct rules that aim to counteract distribution risks. However, the IDD exempts ancillary insurance intermediaries from its scope when they meet certain conditions. The article highlights the regulatory framework on insurance, requiring insurers and intermediaries to address distribution risks, and analyses how this exemption affects the management of distribution risk…

Computer-assisted orientation and drawing of archaeological pottery.

2018

Archaeologists spend considerable time orienting and drawing ceramic fragments by hand for documentation, to infer their manufacture, the nature of the discovery site and its chronology, and to develop hypotheses about commercial and cultural exchanges, social organisation, resource exploitation, and taphonomic processes. This study presents a survey of existing solutions to the time-consuming problem of orienting and drawing pottery fragments. Orientation is based on the 3D geometry of pottery models, which can now be acquired in minutes with low-cost 3D scanners. Several methods are presented: they are based on normal vectors, or circle fittings, or profile fittings. All these methods see…

Spatial pattern analysis using hybrid models: an application to the Hellenic seismicity

2016

Earthquakes are one of the most destructive natural disasters and the spatial distribution of their epi- centres generally shows diverse interaction structures at different spatial scales. In this paper, we use a multi-scale point pattern model to describe the main seismicity in the Hellenic area over the last 10 years. We analyze the interaction between events and the relationship with geo- logical information of the study area, using hybrid models as proposed by Baddeley et al. ( 2013 ). In our analysis, we find two competing suitable hybrid models, one with a full parametric structure and the other one based on nonpara- metric kernel estimators for the spatial inhomogeneity.

Nonparametric estimation of quantile versions of the Lorenz curve

2018

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

2022

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing como…

On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction

2020

Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We consider an approach using a relatively large tolerance for the Markov chain Monte Carlo sampler to ensure its sufficient mixing, and post-processing the output leading to estimators for a range of finer tolerances. We introduce an approximate confidence interval for the related post-corrected estimators, and propose an adaptive approximate Bayesi…