Functional biases in GRB's spectral parameter correlations

Gamma Ray Bursts (GRBs) show evidence of different spectral shapes, light curves, duration, host galaxies and they explode within a wide redshift range. However, the most of them seems to follow very tight correlations among some observed quantities relating to their energetic. If true, these correlations have significant implications on burst physics, giving constraints on theoretical models. Moreover, several suggestions have been made to use these correlations in order to calibrate GRBs as standard candles and to constrain the cosmological parameters. We investigate the cosmological relation between low energy $\alpha$ index in GRBs prompt spectra and the redshift $z$. We present a statistical analysis of the relation between the total isotropic energy $E_{iso}$ and the peak energy $E_p$ (also known as Amati relation) in GRBs spectra searching for possible functional biases. Possible implications on the $E_{iso}$ vs $E_p$ relation of the $\alpha$ vs $(1+z)$ correlation are evaluated. We used MonteCarlo simulations and the boostrap method to evaluate how large are the effects of functional biases on the $E_{iso}$ vs $E_p$. We show that high values of the linear correlation coefficent, up to about 0.8, in the $E_{iso}$ vs $E_p$ relation are obtained for random generated samples of GRBs, confirming the relevance of functional biases. Astrophysical consequences from $E_{iso}$ vs $E_p$ relation are then to be revised after a more accurate and possibly bias free analysis.Comment: 6 pages, 6 figures, conference poster session: "070228: The Next Decade of Gamma-Ray Burst Afterglows", Amsterdam, March 2007, MNRAS submitte

Functional delta residuals and applications to functional effect sizes

Given a functional central limit (fCLT) and a parameter transformation, we use the functional delta method to construct random processes, called functional delta residuals, which asymptotically have the same covariance structure as the transformed limit process. Moreover, we prove a multiplier bootstrap fCLT theorem for these transformed residuals and show how this can be used to construct simultaneous confidence bands for transformed functional parameters. As motivation for this methodology, we provide the formal application of these residuals to a functional version of the effect size parameter Cohen's $d$, a problem appearing in current brain imaging applications. The performance and necessity of such residuals is illustrated in a simulation experiment for the covering rate of simultaneous confidence bands for the functional Cohen's $d$ parameter

Some Exact Results on the Ultrametric Overlap Distribution in Mean Field Spin Glass Models (I)

The mean field spin glass model is analyzed by a combination of mathematically rigororous methods and a powerful Ansatz. The method exploited is general, and can be applied to others disordered mean field models such as, e.g., neural networks. It is well known that the probability measure of overlaps among replicas carries the whole physical content of these models. A functional order parameter of Parisi type is introduced by rigorous methods, according to previous works by F. Guerra. By the Ansatz that the functional order parameter is the correct order parameter of the model, we explicitly find the full overlap distribution. The physical interpretation of the functional order parameter is obtained, and ultrametricity of overlaps is derived as a natural consequence of a branching diffusion process. It is shown by explicit construction that ultrametricity of the 3-replicas overlap distribution together with the Ghirlanda-Guerra relations determines the distribution of overlaps among s replicas, for any s, in terms of the one-overlap distribution.Comment: 17 pages, submitted to Euro. Phys. Jou. B Direc