On Multivariate Records from Random Vectors with Independent Components

Let $\boldsymbol{X}_1,\boldsymbol{X}_2,\dots$ be independent copies of a random vector $\boldsymbol{X}$ with values in $\mathbb{R}^d$ and with a continuous distribution function. The random vector $\boldsymbol{X}_n$ is a complete record, if each of its components is a record. As we require $\boldsymbol{X}$ to have independent components, crucial results for univariate records clearly carry over. But there are substantial differences as well: While there are infinitely many records in case $d=1$, there occur only finitely many in the series if $d\geq 2$. Consequently, there is a terminal complete record with probability one. We compute the distribution of the random total number of complete records and investigate the distribution of the terminal record. For complete records, the sequence of waiting times forms a Markov chain, but differently from the univariate case, now the state infinity is an absorbing element of the state space

Some Results on Joint Record Events

Let $X_1,X_2,\dots$ be independent and identically distributed random variables on the real line with a joint continuous distribution function $F$. The stochastic behavior of the sequence of subsequent records is well known. Alternatively to that, we investigate the stochastic behavior of arbitrary $X_j,X_k,j<k$, under the condition that they are records, without knowing their orders in the sequence of records. The results are completely different. In particular it turns out that the distribution of $X_k$, being a record, is not affected by the additional knowledge that $X_j$ is a record as well. On the contrary, the distribution of $X_j$, being a record, is affected by the additional knowledge that $X_k$ is a record as well. If $F$ has a density, then the gain of this additional information, measured by the corresponding Kullback-Leibler distance, is $j/k$, independent of $F$. We derive the limiting joint distribution of two records, which is not a bivariate extreme value distribution. We extend this result to the case of three records. In a special case we also derive the limiting joint distribution of increments among records

Accuracy of core mass estimates in simulated observations of dust emission

We study the reliability of mass estimates obtained for molecular cloud cores using sub-millimetre and infrared dust emission. We use magnetohydrodynamic simulations and radiative transfer to produce synthetic observations with spatial resolution and noise levels typical of Herschel surveys. We estimate dust colour temperatures using different pairs of intensities, calculate column densities and compare the estimated masses with the true values. We compare these results to the case when all five Herschel wavelengths are available. We investigate the effects of spatial variations of dust properties and the influence of embedded heating sources. Wrong assumptions of dust opacity and its spectral index beta can cause significant systematic errors in mass estimates. These are mainly multiplicative and leave the slope of the mass spectrum intact, unless cores with very high optical depth are included. Temperature variations bias colour temperature estimates and, in quiescent cores with optical depths higher than for normal stable cores, masses can be underestimated by up to one order of magnitude. When heated by internal radiation sources the observations recover the true mass spectra. The shape, although not the position, of the mass spectrum is reliable against observational errors and biases introduced in the analysis. This changes only if the cores have optical depths much higher than expected for basic hydrostatic equilibrium conditions. Observations underestimate the value of beta whenever there are temperature variations along the line of sight. A bias can also be observed when the true beta varies with wavelength. Internal heating sources produce an inverse correlation between colour temperature and beta that may be difficult to separate from any intrinsic beta(T) relation of the dust grains. This suggests caution when interpreting the observed mass spectra and the spectral indices.Comment: Revised version, 17 pages, 17 figures, submitted to A&

Statistical Modeling of Spatial Extremes

The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection. This article reviews recent progress in the statistical modeling of spatial extremes, starting with sketches of the necessary elements of extreme value statistics and geostatistics. The main types of statistical models thus far proposed, based on latent variables, on copulas and on spatial max-stable processes, are described and then are compared by application to a data set on rainfall in Switzerland. Whereas latent variable modeling allows a better fit to marginal distributions, it fits the joint distributions of extremes poorly, so appropriately-chosen copula or max-stable models seem essential for successful spatial modeling of extremes.Comment: Published in at http://dx.doi.org/10.1214/11-STS376 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Rejoinder to "Statistical Modeling of Spatial Extremes"

Rejoinder to "Statistical Modeling of Spatial Extremes" by A. C. Davison, S. A. Padoan and M. Ribatet [arXiv:1208.3378].Comment: Published in at http://dx.doi.org/10.1214/12-STS376REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Corona Australis cloud filament seen in NIR scattered light I. Comparison with extinction of background stars

With current near-infrared (NIR) instruments the near-infrared light scattered from interstellar clouds can be mapped over large areas. The surface brightness carries information on the line-of-sight dust column density. Therefore, scattered light could provide an important tool to study mass distribution in quiescent interstellar clouds at a high, even sub-arcsecond resolution. We wish to confirm the assumption that light scattering dominates the surface brightness in all NIR bands. Furthermore, we want to show that scattered light can be used for an accurate estimation of dust column densities in clouds with Av in the range 1-15mag. We have obtained NIR images of a quiescent filament in the Corona Australis molecular cloud. The observations provide maps of diffuse surface brightness in J, H, and Ks bands. Using the assumption that signal is caused by scattered light we convert surface brightness data into a map of dust column density. The same observations provide colour excesses for a large number of background stars. These data are used to derive an extinction map of the cloud. The two, largely independent tracers of the cloud structure are compared. Results. In regions below Av=15m both diffuse surface brightness and background stars lead to similar column density estimates. The existing differences can be explained as a result of normal observational errors and bias in the sampling of extinctions provided by the background stars. There is no indication that thermal dust emission would have a significant contribution even in the Ks band. The results show that, below Av=15mag, scattered light does provide a reliable way to map cloud structure. Compared with the use of background stars it can also in practice provide a significantly higher spatial resolution.Comment: 14 pages, 15 figures, accepted to A&A, the version includes small changes in the text and an added appendi

The Density Variance Mach Number Relation in the Taurus Molecular Cloud

Supersonic turbulence in molecular clouds is a key agent in generating density enhancements that may subsequently go on to form stars. The stronger the turbulence - the higher the Mach number - the more extreme the density fluctuations are expected to be. Numerical models predict an increase in density variance with rms Mach number of the form: sigma^{2}_{rho/rho_{0}} = b^{2}M^{2}, where b is a numerically-estimated parameter, and this prediction forms the basis of a large number of analytic models of star formation. We provide an estimate of the parameter b from 13CO J=1-0 spectral line imaging observations and extinction mapping of the Taurus molecular cloud, using a recently developed technique that needs information contained solely in the projected column density field to calculate sigma^{2}_{rho/rho_{0}}. We find b ~ 0.48, which is consistent with typical numerical estimates, and is characteristic of turbulent driving that includes a mixture of solenoidal and compressive modes. More conservatively, we constrain b to lie in the range 0.3-0.8, depending on the influence of sub-resolution structure and the role of diffuse atomic material in the column density budget. We also report a break in the Taurus column density power spectrum at a scale of ~1pc, and find that the break is associated with anisotropy in the power spectrum. The break is observed in both 13CO and dust extinction power spectra, which, remarkably, are effectively identical despite detailed spatial differences between the 13CO and dust extinction maps. [ abridged ]Comment: 8 pages, 9 figures. Accepted for publication in A&

Simulating Supersonic Turbulence in Magnetized Molecular Clouds

We present results of large-scale three-dimensional simulations of weakly magnetized supersonic turbulence at grid resolutions up to 1024^3 cells. Our numerical experiments are carried out with the Piecewise Parabolic Method on a Local Stencil and assume an isothermal equation of state. The turbulence is driven by a large-scale isotropic solenoidal force in a periodic computational domain and fully develops in a few flow crossing times. We then evolve the flow for a number of flow crossing times and analyze various statistical properties of the saturated turbulent state. We show that the energy transfer rate in the inertial range of scales is surprisingly close to a constant, indicating that Kolmogorov's phenomenology for incompressible turbulence can be extended to magnetized supersonic flows. We also discuss numerical dissipation effects and convergence of different turbulence diagnostics as grid resolution refines from 256^3 to 1024^3 cells.Comment: 10 pages, 3 figures, to appear in the proceedings of the DOE/SciDAC 2009 conferenc

A method for reconstructing the PDF of a 3D turbulent density field from 2D observations

We introduce a method for calculating the probability density function (PDF) of a turbulent density field in three dimensions using only information contained in the projected two-dimensional column density field. We test the method by applying it to numerical simulations of hydrodynamic and magnetohydrodynamic turbulence in molecular clouds. To a good approximation, the PDF of log(normalised column density) is a compressed, shifted version of the PDF of log(normalised density). The degree of compression can be determined observationally from the column density power spectrum, under the assumption of statistical isotropy of the turbulence.Comment: 5 pages, 2 figures, accepted for publication in MNRAS Letter