Flexible modelling in statistics: past, present and future

In times where more and more data become available and where the data exhibit rather complex structures (significant departure from symmetry, heavy or light tails), flexible modelling has become an essential task for statisticians as well as researchers and practitioners from domains such as economics, finance or environmental sciences. This is reflected by the wealth of existing proposals for flexible distributions; well-known examples are Azzalini's skew-normal, Tukey's $g$-and-$h$, mixture and two-piece distributions, to cite but these. My aim in the present paper is to provide an introduction to this research field, intended to be useful both for novices and professionals of the domain. After a description of the research stream itself, I will narrate the gripping history of flexible modelling, starring emblematic heroes from the past such as Edgeworth and Pearson, then depict three of the most used flexible families of distributions, and finally provide an outlook on future flexible modelling research by posing challenging open questions.Comment: 27 pages, 4 figure

Rectification of a whole-sky photograph as a tool for determining spatial positioning of cumulus clouds

There are no author-identified significant results in this report

Semiconductor manufacturing simulation design and analysis with limited data

This paper discusses simulation design and analysis for Silicon Carbide (SiC) manufacturing operations management at New York Power Electronics Manufacturing Consortium (PEMC) facility. Prior work has addressed the development of manufacturing system simulation as the decision support to solve the strategic equipment portfolio selection problem for the SiC fab design [1]. As we move into the phase of collecting data from the equipment purchased for the PEMC facility, we discuss how to redesign our manufacturing simulations and analyze their outputs to overcome the challenges that naturally arise in the presence of limited fab data. We conclude with insights on how an approach aimed to reflect learning from data can enable our discrete-event stochastic simulation to accurately estimate the performance measures for SiC manufacturing at the PEMC facility

The Giraffe Inner Bulge Survey (GIBS) II. Metallicity distributions and alpha element abundances at fixed Galactic latitude

High resolution (R$\sim$22,500) spectra for 400 red clump giants, in four fields within $\rm -4.8^{\circ} \lesssim b \lesssim -3.4^{\circ}$ and $\rm -10^{\circ} \lesssim l \lesssim +10^{\circ}$, were obtained within the GIRAFFE Inner Bulge Survey (GIBS) project. To this sample we added another $\sim$ 400 stars in Baade's Window, observed with the identical instrumental configuration. We constructed the metallicity distributions for the entire sample, as well as for each field individually, in order to investigate the presence of gradients or field-to-field variations in the shape of the distributions. The metallicity distributions in the five fields are consistent with being drawn from a single parent population, indicating the absence of a gradient along the major axis of the Galactic bar. The global metallicity distribution is well fitted by two Gaussians. The metal poor component is rather broad, with a mean at $\rm =-0.31$ dex and $\sigma=0.31$ dex. The metal-rich one is narrower, with mean $\rm =+0.26$ and $\sigma=0.2$ dex. The [Mg/Fe] ratio follows a tight trend with [Fe/H], with enhancement with respect to solar in the metal-poor regime, similar to the one observed for giant stars in the local thick disc. [Ca/Fe] abundances follow a similar trend, but with a considerably larger scatter than [Mg/Fe]. A decrease in [Mg/Fe] is observed at $\rm [Fe/H]=-0.44$ dex. This \textit{knee} is in agreement with our previous bulge study of K-giants along the minor axis, but is 0.1 dex lower in metallicity than the one reported for the Bulge micro lensed dwarf and sub-giant stars. We found no variation in $\alpha$-element abundance distributions between different fields.Comment: Accepted for publication in A&

Quenching or Bursting: Star Formation Acceleration--A New Methodology for Tracing Galaxy Evolution

We introduce a new methodology for the direct extraction of galaxy physical parameters from multi-wavelength photometry and spectroscopy. We use semi-analytic models that describe galaxy evolution in the context of large scale cosmological simulation to provide a catalog of galaxies, star formation histories, and physical parameters. We then apply stellar population synthesis models and a simple extinction model to calculate the observable broad-band fluxes and spectral indices for these galaxies. We use a linear regression analysis to relate physical parameters to observed colors and spectral indices. The result is a set of coefficients that can be used to translate observed colors and indices into stellar mass, star formation rate, and many other parameters, including the instantaneous time derivative of the star formation rate which we denote the {\it Star Formation Acceleration (SFA)}, We apply the method to a test sample of galaxies with GALEX photometry and SDSS spectroscopy, deriving relationships between stellar mass, specific star formation rate, and star formation acceleration. We find evidence for a mass-dependent SFA in the green valley, with low mass galaxies showing greater quenching and higher mass galaxies greater bursting. We also find evidence for an increase in average quenching in galaxies hosting AGN. A simple scenario in which lower mass galaxies accrete and become satellite galaxies, having their star forming gas tidally and/or ram-pressure stripped, while higher mass galaxies receive this gas and react with new star formation can qualitatively explain our results.Comment: 33 pages, 31 figures, ApJ accepte