background: in survival studies when the event times are dependent, performing of the analysis by using of methods based on independent assumption, leads to biased. in this paper, using copula function and considering the dependence structure between the event times, a parametric joint distribution has made fitting to the events, and the effective factors on each of these events would be determ...

Using kernel density estimation and mixture models, household size-adjusted income distributions in Italy are cross-sectionally examined over the period 1987-2000. Nonparametric tests assess the shape time invariance and the presence of modes in the distributions. Evidence shows that income tend to cluster around more than one point, giving good reasons to model the shapes by a finite mixture d...

MARCH 2003 THE JOURNAL OF FIXED INCOME 81 V alue at risk modelers face difficult trade-offs in choosing between the two major VaR methodologies: historical/ Monte Carlo simulations or parametric models. The historical approach uses the recent history of the asset price (or, for derivatives, the price of the underlying), while the parametric approach imposes functional form assumptions upon the ...

Continuous data arise in most areas of medicine. Familiar clinical examples include blood pressure, ejection fraction, forced expiratory volume in 1 second (FEV1), serum cholesterol, and anthropometric measurements. Methods for analysing continuous data fall into two classes, distinguished by whether or not they make assumptions about the distribution of the data. Theoretical distributions are ...

Introduction Diffusion imaging enables microscopic assessment of tissue structure by measuring the displacement of water molecules. Several models have been proposed to relate diffusion weighted MR signals and various structural features of the tissue. One recent model, the composite hindered and restricted model of diffusion (CHARMED), was shown to be able to extract white matter fiber orienta...

We report the first measurement of the joint photon-number probability distribution for a two-mode quantum state created by a nondegenerate optical parametric amplifier. The measured distributions exhibit up to 1.9 dB of quantum correlation between the signal and idler photon numbers, whereas the marginal distributions are thermal as expected for parametric fluorescence.

We describe a maximum-likelihood method for determining the mass distribution in spherical stellar systems from the radial velocities of a population of discrete test particles. The method assumes a parametric form for the mass distribution and a non-parametric two-integral distribution function. We apply the method to a sample of 161 globular clusters in M87. We find that the mass within 32 kp...

This study compared the relative statistical sensitivity of non-parametric and parametric statistics of 3-dimensional current sources as estimated by the EEG inverse solution Low Resolution Electromagnetic Tomography (LORETA). One would expect approximately 5% false positives (classification of a normal as abnormal) at the P < .025 level of probability (two tailed test) and approximately 1% fal...

In this paper, we establish sharp bounds on the joint distribution of potential outcomes and the distribution of treatment effects in parametric switching regimes models with generalized hyperbolic errors and in the semiparametric switching regimes models of Heckman (1990). Our results for parametric switching regimes models with generalized hyperbolic errors extend some existing results for Ga...

Glossary Hypothesis A hypothesis is a statement concerning the (joint) distribution underlying the observed data. Nonparametric test In contrast to a parametric test, a nonparametric test does not presume a particular parametric structure concerning the data generating process. Serial dependence Statistical dependence among time series observations.