相关论文: Regional economic convergence and spatial quantile…

This paper introduces a novel spatial scalar-on-function quantile regression model that extends classical scalar-on-function models to account for spatial dependence and heterogeneous conditional distributions. The proposed model…

In this paper I introduce quantile spectral densities that summarize the cyclical behavior of time series across their whole distribution by analyzing periodicities in quantile crossings. This approach can capture systematic changes in the…

This paper introduces a causal machine learning approach to investigate the impact of the EU-Canada Comprehensive Economic Trade Agreement (CETA). We propose a matrix completion algorithm on French customs data to obtain multidimensional…

This study aims to improve the spatial representation of uncertainties when regressing surface wind speeds from large-scale atmospheric predictors for sub-seasonal forecasting. Sub-seasonal forecasting often relies on large-scale…

This paper investigates the presence of long memory in corporate bond and stock indices of six European Union countries from July 1998 to February 2015. We compute the Hurst exponent by means of the DFA method and using a sliding window in…

An innovative method is proposed to construct a quantile dependence system for inflation and money growth. By considering all quantiles and leveraging a novel notion of quantile sensitivity, the method allows the assessment of changes in…

Many studies have shown that there are good reasons to claim very low predictability of currency nevertheless, the deviations from true randomness exist which have potential predictive and prognostic power [J.James, Quantitative finance 3…

Urban sprawl reshapes cities, yet its quantitative laws remain elusive. Analyzing built-up expansion in 19 cities (1985-2015) with tools from surface growth physics in radial geometry, we reveal anisotropic, branch-like growth and a…

With the rapid advances of data acquisition techniques, spatio-temporal data are becoming increasingly abundant in a diverse array of disciplines. Here we develop spatio-temporal regression methodology for analyzing large amounts of…

An integrated European Research Area (ERA) is a critical component for a more competitive and open European R&D system. However, the impact of EU-specific integration policies aimed at overcoming innovation barriers associated with national…

A robust estimator is proposed for the parameters that characterize the linear regression problem. It is based on the notion of shrinkages, often used in Finance and previously studied for outlier detection in multivariate data. A thorough…

Quantile regression, the prediction of conditional quantiles, finds applications in various fields. Often, some or all of the variables are discrete. The authors propose two new quantile regression approaches to handle such mixed…

Neural networks have revolutionized many empirical fields, yet their application to financial time series forecasting remains controversial. In this study, we demonstrate that the conventional practice of estimating models locally in…

The fall of the Berlin Wall in 1989, modified the relations between cities of the former communist bloc. The European and worldwide reorientation of interactions that followed raises the question of the actual state of historical…

During the last decades, public policies become a central pillar in supporting and stabilising agricultural sector. In 1962, EU policy-makers developed the so-called Common Agricultural Policy (CAP) to ensure competitiveness and a common…

Environmental and climate processes are often distributed over large space-time domains. Their complexity and the amount of available data make modelling and analysis a challenging task. Statistical modelling of environment and climate data…

Extremiles provide a generalization of quantiles which are not only robust, but also have an intrinsic link with extreme value theory. This paper introduces an extremile regression model tailored for functional covariate spaces. The…

We use a new method of studying the Hurst exponent with time and scale dependency. This new approach allow us to recover the major events affecting worldwide markets (such as the September 11th terrorist attack) and analyze the way those…

Kulldorff's (1997) seminal paper on spatial scan statistics (SSS) has led to many methods considering different regions of interest, different statistical models, and different approximations while also having numerous applications in…

Socio-economic inequalities derived from an exhaustive wealth distribution is studied in a closed geographical region from Transylvania (Romania). Exhaustive wealth data is computed from the agricultural records of the Sancraiu commune for…