... Default . ... The descriptions below focus on the meaning of each filename parameter, leaving the exact details of the inferred default value to be explained in the algorithm section. evlist . ... file . The response matrix file (OGIP-compliant format). ... If a spectrum file is not provided ( withspectrum =no) this parameter specifies the INDEX number of a source in the source description list (parameter srclist ), and thereby the incidence angle and selection regions for the response matrix. ...

Next: Star Formation Rate and Up: No Title Previous: Calculation of Evolutionary Tracks . To start calculations, we choose the distributions of the initial binary parameters: the mass of the primary ZAMS component, , binary mass ratio, , orbital separation a . ... whereas the mass ratio distribution is not. ... The zero assumption often made is that the mass ratio distribution has a flat shape, that is binaries with a high mass ratio occur as frequently as those with equal masses. ...

Applying Bayesian analysis to polarisation data J. Geisbuesch ( Cambridge ) Bayesian analysis of polarisation data LOFAR MKSP Workshop 1 / 15 Outline 1 2 3 4 Polarisation simulations @ radio wavebands Bayesian analysis Analysis of polarisation data Conclusions J. Geisbuesch ( Cambridge ) Bayesian analysis of polarisation data LOFAR ...

... We demonstrate through numerical simulations that model parameters estimated with our technique are essentially bias-free, even when the average number of counts per bin is 1. ... The IW technique avoids such biases by estimating through successive iterations, where for each iteration, j, , and the best-fit parameters are determined by minimization of . ... In our sample, we find that the minimum values and best-fit parameters converge after about 6 iterations. ...

... casa::Weibull . ... Weibull ( RNG *gen, Double alpha=1.0, Double beta=1.0) . ... alpha () const . ... These function allow you to manipulate the parameters (alpha & beta) described above through the base class. virtual Vector < Double > . ... The Weibull class implements a weibull distribution with parameters alpha and beta . ... Double casa::Weibull::alpha . ... Double casa::Weibull::beta . ... virtual Double casa::Weibull::operator() . ... virtual Vector < Double > casa::Weibull::parameters . ...

... Observers may find that they wish to perform parts of the pipeline reduction again on their data using these tasks. Typical examples will be to re-perform cosmic ray rejection, altering the input parameters or using data from separate datasets, or to perform one-dimensional spectral extraction on long-slit data or to modify the input parameters (e.g., aperture extraction box, or background region) when doing one-dimensional spectral extraction for echelle data. ... Rectify spectral images. ...

... In brief: the frequency-dependent radiative transfer equation is solved for a dust under assumption of spherically-symmetric geometry for its distribution taking into account particle size distribution and quantum heating effects for the very small dust particles. ... Table: Model parameters for IRAS04296+3429. ... parameter . ... hot dust shell) . ... The best fit to the spectral energy distribution of IRAS04296 is shown by heavy solid line (see Table2 for details concerning parameters of the model...

... FTP access the basic models is here . ... Below, we put short descriptions of the used SED models for the photometric redshifts providing by the current server . ... The uniqueness of this model consists in expanding to the near IR (NIR) of Rocca-Volmerange and Guiderdoni's (1988) atlas of synthetic spectra with a revised stellar library, which includes parameters of cool stars. ... Homepage of the GISSEL model). ... Another model used earlier is the model of synthetic spectra of Poggianti (1997). ...

... Archives . ... Reduced and Processed Data . ... 2 distribution plays an incredibly important role in astronomical data analysis, but it is pretty much a black box to most astronomers. ... Comment ( RSS ) | ... I guess in the typical analysis we call chi2 a ?random variable? that follows the chi2 distribution: . ... where D(i) is the observed data, M(i) is the model predicted data and we ?silently? assume that D(i) is normally distributed and each i measurement is independent. ... Chandra Blog . ...