Search results for "parametri"

Multiparametric MRI-based Dosimetric Parameters Best Predict Short-term Time Course of PSA After Iodine 125 Permanent Prostate Implantation for Local…

2012

International audience; D90% and V150% of the entire prostate are recognized as the best dosimetric predictors of outcome after 125 I permanent prostate implantation (PPI). The purpose of this study was 2-fold: 1) to determine the relationship between dose-volume parameters of the Dominant Intraprostatic Lesion (DIL) when compared to the prostate and early biochemical outcome after PPI; 2) to define if dose-volume parameters of the central gland (CG), the peripheral zone (PZ) and the DIL could best predict PSA bounce occurrence. The time course of PSA and mechanisms of bounces still remain unclear after PPI. Patients who had a higher dose in the DIL had a worse PSA level at 1 year which is …

Alternated estimation in semi-parametric space-time branching-type point processes with application to seismic catalogs

2014

An estimation approach for the semi-param-etric intensity function of a class of space-time point processes is introduced. In particular we want to account for the estimation of parametric and nonparametric components simultaneously, applying a forward predictive likelihood to semi-parametric models. For each event, the probability of being a background event or an offspring is therefore estimated.

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.

Estimation de la relation de salaires de Mincer : choix de specification et enjeux économétriques

2012

In the present doctoral thesis, we estimated Mincer’s (1974) semi logarithmic wage function for the French and Pakistani labour force data. This model is considered as a standard tool in order to estimate the relationship between earnings/wages and different contributory factors. Despite of its vide and extensive use, simple estimation of the Mincerian model is biased because of different econometric problems. The main sources of bias noted in the literature are endogeneity of schooling, measurement error, and sample selectivity. We have tackled the endogeneity and measurement error biases via instrumental variables two stage least squares approach for which we have proposed two new instrum…

Orthogonal Multicarrier Transmission with Modal Channel Estimation

2009

A novel multi-carrier orthogonal transmission scheme is presented. While being simpler to implement, it has a spectral efficiency and design parameters similar to those of Orthogonal Frequency Division Multiplexing based on Offset Quadrature Amplitude Modulation (OFDM/OQAM). A parametric channel estimation technique is subsequently reported. The proposed technique is based on an algorithm obtained from classic Multiple Signal Classification (MUSIC) by relaxation of the hypothesis on the number of measurements with respect to the number of sensors. Numerical simulations show that our proposal outperforms previous works in this field.

Nonparametric estimation of quantile versions of the Lorenz curve

2018

Non-parametric probabilistic forecasting of academic performance in Spanish high school using an epidemiological modelling approach

2013

Academic underachievement is a concern of paramount importance in Europe, and particularly in Spain, where around of 30% of the students in the last two courses in high school do not achieve the minimum knowledge academic requirement. In order to analyse this problem, we propose a mathematical model via a system of ordinary differential equations to study the dynamics of the academic performance in Spain. Our approach is based on the idea that both, good and bad study habits, are a mixture of personal decisions and influence of classmates. Moreover, in order to consider the uncertainty in the estimation of model parameters, a bootstrapping approach is employed. This technique permits to for…

Bayesian two-stage regression with parametric heteroscedasticity

2008

In this paper, we expand Kleibergen and Zivot's (2003) Bayesian two-stage (B2S) model by allowing for unequal variances. Our choice for modeling heteroscedasticity is a fully Bayesian parametric approach. As an application, we present a cross-country Cobb–Douglas production function estimation.

Estimation of ordered response models with sample selection

2011

We introduce two new Stata commands for the estimation of an ordered response model with sample selection. The opsel command uses a standard maximum-likelihood approach to fit a parametric specification of the model where errors are assumed to follow a bivariate Gaussian distribution. The snpopsel command uses the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 363–390) to fit a semiparametric specification of the model where the bivariate density function of the errors is approximated by a Hermite polynomial expansion. The snpopsel command extends the set of Stata routines for semi-nonparametric estimation of discrete response models. Compared to the other semi-n…

B-Spline Estimation in a Survey Sampling Framework

2021

Nonparametric regression models have been used more and more over the last years to model survey data and incorporate efficiently auxiliary information in order to improve the estimation of totals, means or other study parameters such as Gini index or poverty rate. B-spline nonparametric regression has the benefit of being very flexible in modeling nonlinear survey data while keeping many similarities and properties of the classical linear regression. This method proved to be efficient for deriving a unique system of weights which allowed to estimate in an efficient way and simultaneously many study parameters. Applications on real and simulated survey data showed its high efficiency. This …