Approximations for two-dimensional discrete scan statistics in some block-factor type dependent models

We consider the two-dimensional discrete scan statistic generated by a block-factor type model obtained from i.i.d. sequence. We present an approximation for the distribution of the scan statistics and the corresponding error bounds. A simulation study illustrates our methodology.Comment: 17 pages, 9 figure

Estimation of noisy cubic spline using a natural basis

We define a new basis of cubic splines such that the coordinates of a natural cubic spline are sparse. We use it to analyse and to extend the classical Schoenberg and Reinsch result and to estimate a noisy cubic spline. We also discuss the choice of the smoothing parameter. All our results are illustrated graphically.Comment: 29 pages, 6 figure

The Romanian Political System after the Parliamentary Elections of November 30, 2008

The article examines the evolution of Romanian politics in the period 1990-2008, discussing the level of participation, the effective number of parties, the electoral performances of the main political forces, the types of government and their parliamentary support

Approximation for the Distribution of Three-dimensional Discrete Scan Statistic

We consider the discrete three dimensional scan statistics. Viewed as the maximum of an 1-dependent stationary r.v.'s sequence, we provide approximations and error bounds for the probability distribution of the three dimensional scan statistics. Importance sampling algorithm is used to obtains sharp bounds for the simulation error. Simulation results and comparisons with other approximations are presented for the binomial and Poisson models

Primele alegeri româneşti

The article describes the first elections organized in the Romanian Principalities based on the Regulamente Organice (a Romanian proto-constitution), namely the legislative elections for the so-called Adunări Ordinare Obşteşti (Ordinary Public Assemblies), but also the election of Gheorghe Bibescu as head of state by the so-called Neobicinuita Obştească Adunare (Extraordinary Public Assembly) in 1842. The article analyzes the genesis of the legal provisions under Russian influence, but also the vote itself. The author reaches the conclusion that modernization begins before the 1848 revolution

Partide, voturi și mandate la alegerile din România (1990-2012)

Since 1992, in the wake of the first elections held in May 1990 and the adoption of a Constitution in 1991, parliamentary and local elections have been held every four years. Romanian electorate voted six times in presidential elections and seven times in referenda (referenda were more numerous than the ones organized during the whole modern history of the country). Reinvented in 1989, Romanian political parties had to pass all these tests. The main purpose of the article is to give a comprehensive, systematic and detailed view on Romanian parties’ performance, both in terms of votes and mandates. Therefore, data is organized following four main criteria: legal status, the mobilization in electoral competitions, parliamentary status, and participation to government

Regression with categorical functional data

International audienceRegression models based on RKHS methods are used to estimate the regression function for scalar response and categorical functional predictor. A simulation study based on paths of a Markov jump process with finite set of states will illustrate the proposed methodology

Al nouălea primar postcomunist al Bucureştiului

The article describes the candidacies and the results of the elections for the Mayor of Bucharest of April the 3rd 2005. The author remarks two aspects: none of the candidates of June 2004 "re"-presented himself in front of the electorate; moreover, several parties did not fulfill the legal specification of obtaining 50 thousands votes in the local and the general elections of 2004

Fusion regression methods with repeated functional data

Linear regression and classification methods with repeated functional data are considered. For each statistical unit in the sample, a real-valued parameter is observed over time under different conditions. Two regression methods based on fusion penalties are presented. The first one is a generalization of the variable fusion methodology based on the 1-nearest neighbor. The second one, called group fusion lasso, assumes some grouping structure of conditions and allows for homogeneity among the regression coefficient functions within groups. A finite sample numerical simulation and an application on EEG data are presented

Classification of multivariate functional data on different domains with Partial Least Squares approaches

Classification (supervised-learning) of multivariate functional data is considered when the elements of the random functional vector of interest are defined on different domains. In this setting, PLS classification and tree PLS-based methods for multivariate functional data are presented. From a computational point of view, we show that the PLS components of the regression with multivariate functional data can be obtained using only the PLS methodology with univariate functional data. This offers an alternative way to present the PLS algorithm for multivariate functional data.Comment: enhance readability, new simulation setting, correction of minor mathematical notations errors, rewrite the conclusio