Results 1351-1400 of 1931 (1899 ASCL, 32 submitted)
The FIBRE-pac (FMOS image-based reduction package) is an IRAF-based reduction tool for the fiber multiple-object spectrograph (FMOS) of the Subaru telescope. To reduce FMOS images, a number of special techniques are necessary because each image contains about 200 separate spectra with airglow emission lines variable in spatial and time domains, and with complicated throughput patterns for the airglow masks. In spite of these features, almost all of the reduction processes except for a few steps are carried out automatically by scripts in text format making it easy to check the commands step by step. Wavelength- and flux-calibrated images together with their noise maps are obtained using this reduction package.
fibmeasure finds the precise locations of the centers of back-illuminated optical fibers in images. It was developed for astronomical fiber positioning feedback via machine vision cameras and is optimized for high-magnification images where fibers appear as resolvable circles. It was originally written during the design of the WEAVE pick-and-place fiber positioner for the William Herschel Telescope.
FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST).
Benchmarks performed on a variety of platforms show that FFTW's performance is typically superior to that of other publicly available FFT software, and is even competitive with vendor-tuned codes. In contrast to vendor-tuned codes, however, FFTW's performance is portable: the same program will perform well on most architectures without modification.
FFTLog is a set of Fortran subroutines that compute the fast Fourier or Hankel (= Fourier-Bessel) transform of a periodic sequence of logarithmically spaced points. FFTLog can be regarded as a natural analogue to the standard Fast Fourier Transform (FFT), in the sense that, just as the normal FFT gives the exact (to machine precision) Fourier transform of a linearly spaced periodic sequence, so also FFTLog gives the exact Fourier or Hankel transform, of arbitrary order m, of a logarithmically spaced periodic sequence.
Fewbody is a numerical toolkit for simulating small-N gravitational dynamics. It is a general N-body dynamics code, although it was written for the purpose of performing scattering experiments, and therefore has several features that make it well-suited for this purpose. Fewbody uses the 8th-order Runge-Kutta Prince-Dormand integration method with 9th-order error estimate and adaptive timestep to advance the N-body system forward in time. It integrates the usual formulation of the N-body equations in configuration space, but allows for the option of global pairwise Kustaanheimo-Stiefel (K-S) regularization (Heggie 1974; Mikkola 1985). The code uses a binary tree algorithm to classify the N-body system into a set of independently bound hierarchies, and performs collisions between stars in the “sticky star” approximation. Fewbody contains a collection of command line utilities that can be used to perform individual scattering and N-body interactions, but is more generally a library of functions that can be used from within other codes.
Fermipy facilitates analysis of data from the Large Area Telescope (LAT) with the Fermi Science Tools. It is built on the pyLikelihood interface of the Fermi Science Tools and provides a set of high-level tools for performing common analysis tasks, including data and model preparation with the gt-tools, extracting a spectral energy distribution (SED) of a source, and generating TS and residual maps for a region of interest. Fermipy also finds new source candidates and can localize a source or fit its spatial extension. The package uses a configuration-file driven workflow in which the analysis parameters (data selection, IRFs, and ROI model) are defined in a YAML configuration file. Analysis is executed through a python script that calls the methods of GTAnalysis to perform different analysis operations.
Bandpass shifting and the (1+z)5 surface brightness dimming (for a fixed width filter) make standard tools for the extraction of structural parameters of galaxies wavelength dependent. If only few (or one) observed high-res bands exist, this dependence has to be corrected to make unbiased statements on the evolution of structural parameters or on galaxy subsamples defined by morphology. FERENGI artificially redshifts low-redshift galaxy images to different redshifts by applying the correct cosmological corrections for size, surface brightness and bandpass shifting. A set of artificially redshifted galaxies in the range 0.1<z<1.1 using a set of ~100 SDSS low-redshift (v<7000 km s-1) images as input has been created to use as a training set of realistic images of galaxies of diverse morphologies and a large range of redshifts for the GEMS and COSMOS galaxy evolution projects. This training set allows other studies to investigate and quantify the effects of cosmological redshift on the determination of galaxy morphologies, distortions, and other galaxy properties that are potentially sensitive to resolution, surface brightness, and bandpass issues. The data sets are also available for download from the FERENGI website.
feets characterizes and analyzes light-curves from astronomical photometric databases for modelling, classification, data cleaning, outlier detection and data analysis. It uses machine learning algorithms to determine the numerical descriptors that characterize and distinguish the different variability classes of light-curves; these range from basic statistical measures such as the mean or standard deviation to complex time-series characteristics such as the autocorrelation function. The library is not restricted to the astronomical field and could also be applied to any kind of time series. This project is a derivative work of FATS (ascl:1711.017).
FDPS provides the necessary functions for efficient parallel execution of particle-based simulations as templates independent of the data structure of particles and the functional form of the interaction. It is used to develop particle-based simulation programs for large-scale distributed-memory parallel supercomputers. FDPS includes templates for domain decomposition, redistribution of particles, and gathering of particle information for interaction calculation. It uses algorithms such as Barnes-Hut tree method for long-range interactions; methods to limit the calculation to neighbor particles are used for short-range interactions. FDPS reduces the time and effort necessary to write a simple, sequential and unoptimized program of O(N^2) calculation cost, and produces compiled programs that will run efficiently on large-scale parallel supercomputers.
FDIPS is a finite difference iterative potential-field solver that can generate the 3D potential magnetic field solution based on a magnetogram. It is offered as an alternative to the spherical harmonics approach, as when the number of spherical harmonics is increased, using the raw magnetogram data given on a grid that is uniform in the sine of the latitude coordinate can result in inaccurate and unreliable results, especially in the polar regions close to the Sun. FDIPS is written in Fortran 90 and uses the MPI library for parallel execution.
FDBinary disentangles spectra of SB2 stars. The spectral disentangling technique can be applied on a time series of observed spectra of an SB2 to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. The code is written in C and is designed as a command-line utility for a Unix-like operating system. FDBinary uses the Fourier-space approach in separation of composite spectra. This code has been replaced with the newer fd3 (ascl:1705.012).
The spectral disentangling technique can be applied on a time series of observed spectra of a spectroscopic double-lined binary star (SB2) to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. fd3 disentangles the spectra of SB2 stars, capable also of resolving the possible third companion. It performs the separation of spectra in the Fourier space which is faster, but in several respects less versatile than the wavelength-space separation. (Wavelength-space separation is implemented in the twin code CRES.) fd3 is written in C and is designed as a command-line utility for a Unix-like operating system. fd3 is a new version of FDBinary (ascl:1705.011), which is now deprecated.
fcmaker creates astronomical finding charts for Observing Blocks (OBs) on the p2 web server from the European Southern Observatory (ESO). It automates the creation of ESO-compliant finding charts for Service Mode and/or Visitor Mode OBs at the Very Large Telescope (VLT). The design of the fcmaker finding charts, based on an intimate knowledge of VLT observing procedures, is fine-tuned to best support night time operations. As an automated tool, fcmaker also allows observers to independently check visually, for the first time, the observing sequence coded inside an OB. This includes, for example, the signs of telescope and position angle offsets.
FCLC (Featureless Classification of Light Curves) software describes the static behavior of a light curve in a probabilistic way. Individual data points are converted to densities and consequently probability density are compared instead of features. This gives rise to an independent classification which can corroborate the usefulness of the selected features.
FBEYE, the "Flares By-Eye" detection suite, is written in IDL and analyzes Kepler light curves and validates flares. It works on any 3-column light curve that contains time, flux, and error. The success of flare identification is highly dependent on the smoothing routine, which may not be suitable for all sources.
FATS facilitates and standardizes feature extraction for time series data; it quickly and efficiently calculates a compilation of many existing light curve features. Users can characterize or analyze an astronomical photometric database, though this library is not necessarily restricted to the astronomical domain and can also be applied to any kind of time series data.
FAT (Fully Automated TiRiFiC) is an automated procedure that fits tilted-ring models to Hi data cubes of individual, well-resolved galaxies. The method builds on the 3D Tilted Ring Fitting Code (TiRiFiC, ascl:1208.008). FAT accurately models the kinematics and the morphologies of galaxies with an extent of eight beams across the major axis in the inclination range 20°-90° without the need for priors such as disc inclination. FAT's performance allows us to model the gas kinematics of many thousands of well-resolved galaxies, which is essential for future HI surveys, with the Square Kilometre Array and its pathfinders.
PSF fitting photometry allows a simultaneously fit of a PSF profile on the sources. Many routines use PSF fitting photometry, including IRAF/allstar, Strarfinder, and Convphot. These routines are in general complex to use and slow. FASTPHOT is optimized for prior extraction (the position of the sources is known) and is very fast and simple.
The analysis of weak lensing data requires to account for missing data such as masking out of bright stars. To date, the majority of lensing analyses uses the two point-statistics of the cosmic shear field. These can either be studied directly using the two-point correlation function, or in Fourier space, using the power spectrum. The two-point correlation function is unbiased by missing data but its direct calculation will soon become a burden with the exponential growth of astronomical data sets. The power spectrum is fast to estimate but a mask correction should be estimated. Other statistics can be used but these are strongly sensitive to missing data. The solution that is proposed by FASTLens is to properly fill-in the gaps with only NlogN operations, leading to a complete weak lensing mass map from which one can compute straight forwardly and with a very good accuracy any kind of statistics like power spectrum or bispectrum.
Because of their simplicity, axisymmetric mass distributions are often used to model gravitational lenses. Since galaxies are usually observed to have elliptical light distributions, mass distributions with elliptical density contours offer more general and realistic lens models. They are difficult to use, however, since previous studies have shown that the deflection angle (and magnification) in this case can only be obtained by rather expensive numerical integrations. We present a family of lens models for which the deflection can be calculated to high relative accuracy (10-5) with a greatly reduced numerical effort, for small and large ellipticity alike. This makes it easier to use these distributions for modeling individual lenses as well as for applications requiring larger computing times, such as statistical lensing studies. FASTELL is a code to calculate quickly and accurately the lensing deflection and magnification matrix for the softened power-law elliptical mass distribution (SPEMD) lens galaxy model. The SPEMD consists of a softened power-law radial distribution with elliptical isodensity contours.
The Fast Chi-Squared Algorithm is a fast, powerful technique for detecting periodicity. It was developed for analyzing variable stars, but is applicable to many of the other applications where the Fast Fourier Transforms (FFTs) or other periodograms (such as Lomb-Scargle) are currently used. The Fast Chi-squared technique takes a data set (e.g. the brightness of a star measured at many different times during a series of observations) and finds the periodic function that has the best frequency and shape (to an arbitrary number of harmonics) to fit the data. Among its advantages are:
FastChem is an equilibrium chemistry code that calculates the chemical composition of the gas phase for given temperatures and pressures. Written in C++, it is based on a semi-analytic approach, and is optimized for extremely fast and accurate calculations.
FAST (Fitting and Assessment of Synthetic Templates) fits stellar population synthesis templates to broadband photometry and/or spectra. FAST is compatible with the photometric redshift code EAzY (ascl:1010.052) when fitting broadband photometry; it uses the photometric redshifts derived by EAzY, and the input files (for examply, photometric catalog and master filter file) are the same. FAST fits spectra in combination with broadband photometric data points or simultaneously fits two components, allowing for an AGN contribution in addition to the host galaxy light. Depending on the input parameters, FAST outputs the best-fit redshift, age, dust content, star formation timescale, metallicity, stellar mass, star formation rate (SFR), and their confidence intervals. Though some of FAST's functions overlap with those of HYPERZ (ascl:1108.010), it differs by fitting fluxes instead of magnitudes, allows the user to completely define the grid of input stellar population parameters and easily input photometric redshifts and their confidence intervals, and calculates calibrated confidence intervals for all parameters. Note that FAST is not a photometric redshift code, though it can be used as one.
FAST-PT calculates 1-loop corrections to the matter power spectrum in cosmology. The code utilizes Fourier methods combined with analytic expressions to reduce the computation time down to scale as N log N, where N is the number of grid point in the input linear power spectrum. FAST-PT is extremely fast, enabling mode-coupling integral computations fast enough to embed in Monte Carlo Markov Chain parameter estimation.
We place functional constraints on the shape of the inflaton potential from the cosmic microwave background through a variant of the generalized slow roll approximation that allows large amplitude, rapidly changing deviations from scale-free conditions. Employing a principal component decomposition of the source function G'~3(V'/V)^2 - 2V''/V and keeping only those measured to better than 10% results in 5 nearly independent Gaussian constraints that maybe used to test any single-field inflationary model where such deviations are expected. The first component implies < 3% variations at the 100 Mpc scale. One component shows a 95% CL preference for deviations around the 300 Mpc scale at the ~10% level but the global significance is reduced considering the 5 components examined. This deviation also requires a change in the cold dark matter density which in a flat LCDM model is disfavored by current supernova and Hubble constant data and can be tested with future polarization or high multipole temperature data. Its impact resembles a local running of the tilt from multipoles 30-800 but is only marginally consistent with a constant running beyond this range. For this analysis, we have implemented a ~40x faster WMAP7 likelihood method which we have made publicly available.
The Fast Template Periodogram extends the Generalised Lomb Scargle periodogram (Zechmeister and Kurster 2009) for arbitrary (periodic) signal shapes. A template is first approximated by a truncated Fourier series of length H. The Nonequispaced Fast Fourier Transform NFFT is used to efficiently compute frequency-dependent sums. Template fitting can now be done in NlogN time, improving existing algorithms by an order of magnitude for even small datasets. The FTP can be used in conjunction with gradient descent to accelerate a non-linear model fit, or be used in place of the multi-harmonic periodogram for non-sinusoidal signals with a priori known shapes.
A successor of FARGO (ascl:1102.017), FARGO3D is a versatile HD/MHD code that runs on clusters of CPUs or GPUs, with special emphasis on protoplanetary disks. FARGO3D offers Cartesian, cylindrical or spherical geometry; 1-, 2- or 3-dimensional calculations; and orbital advection (aka FARGO) for HD and MHD calculations. As in FARGO, a simple Runge-Kutta N-body solver may be used to describe the orbital evolution of embedded point-like objects. There is no need to know CUDA; users can develop new functions in C and have them translated to CUDA automatically to run on GPUs.
FARGO is an efficient and simple modification of the standard transport algorithm used in explicit eulerian fixed polar grid codes, aimed at getting rid of the average azimuthal velocity when applying the Courant condition. This results in a much larger timestep than the usual procedure, and it is particularly well-suited to the description of a Keplerian disk where one is traditionally limited by the very demanding Courant condition on the fast orbital motion at the inner boundary. In this modified algorithm, the timestep is limited by the perturbed velocity and by the shear arising from the differential rotation. The speed-up resulting from the use of the FARGO algorithm is problem dependent. In the example presented in the code paper below, which shows the evolution of a Jupiter sized protoplanet embedded in a minimum mass protoplanetary nebula, the FARGO algorithm is about an order of magnitude faster than a traditional transport scheme, with a much smaller numerical diffusivity.
FAMIAS (Frequency Analysis and Mode Identification for Asteroseismology) is a package of software tools programmed in C++ for the analysis of photometric and spectroscopic time-series data. FAMIAS provides analysis tools that are required for the steps between the data reduction and the seismic modeling. Two main sets of tools are incorporated in FAMIAS. The first set permits to search for periodicities in the data using Fourier and non-linear least-squares fitting techniques. The other set permits to carry out a mode identification for the detected pulsation frequencies to determine their harmonic degree l, and azimuthal order m. FAMIAS is applicable to main-sequence pulsators hotter than the Sun. This includes Gamma Dor, Delta Sct stars, slowly pulsating B (SPB)-stars and Beta Cep stars - basically all stars for which empirical mode identification is required to successfully carry out asteroseismology.
FAMA (Fast Automatic MOOG Analysis), written in Perl, computes the atmospheric parameters and abundances of a large number of stars using measurements of equivalent widths (EWs) automatically and independently of any subjective approach. Based on the widely-used MOOG code, it simultaneously searches for three equilibria, excitation equilibrium, ionization balance, and the relationship between logn(FeI) and the reduced EWs. FAMA also evaluates the statistical errors on individual element abundances and errors due to the uncertainties in the stellar parameters. Convergence criteria are not fixed "a priori" but instead are based on the quality of the spectra.
FalconIC generates discrete particle positions, velocities, masses and pressures based on linear Boltzmann solutions that are computed by libraries such as CLASS and CAMB. FalconIC generates these initial conditions for any species included in the selection, including Baryons, Cold Dark Matter and Dark Energy fluids. Any species can be set in Eulerian (on a fixed grid) or Lagrangian (particle motion) representation, depending on the gauge and reality chosen. That is, for relativistic initial conditions in the synchronous comoving gauge, Dark Matter can only be described in an Eulerian representation. For all other choices (Relativistic in Longitudinal gauge, Newtonian with relativistic expansion rates, Newtonian without any notion of radiation), all species can be treated in all representations. The code also computes spectra. FalconIC is useful for comparative studies on initial conditions.
FAC calculates various atomic radiative and collisional processes, including radiative transition rates, collisional excitation and ionization by electron impact, energy levels, photoionization, and autoionization, and their inverse processes radiative recombination and dielectronic capture. The package also includes a collisional radiative model to construct synthetic spectra for plasmas under different physical conditions.
Light curves from the Kepler telescope rely on "postage stamp" cutouts of a few pixels near each of 200,000 target stars. These light curves are optimized for the detection of short-term signals like planet transits but induce systematics that overwhelm long-term variations in stellar flux. Longer-term effects can be recovered through analysis of the Full Frame Images, a set of calibration data obtained monthly during the Kepler mission. The Python package f3 analyzes the Full Frame Images to infer long-term astrophysical variations in the brightness of Kepler targets, such as magnetic activity or sunspots on slowly rotating stars.
EzGal is a flexible Python program which generates observable parameters (magnitudes, colors, and mass-to-light ratios) for arbitrary input stellar population synthesis (SPS) models; it enables simple, direct comparison of different model sets so that the uncertainty introduced by choice of model set can be quantified. EzGal is also capable of generating composite stellar population models (CSPs) for arbitrary input star-formation histories and reddening laws, and can be used to interpolate between metallicities for a given model set.
EZ (Easy-Z) estimates redshifts for extragalactic objects. It compares the observed spectrum with a set of (user given) spectral templates to find out the best value for the redshift. To accomplish this task, it uses a highly configurable set of algorithms. EZ is easily extendible with new algorithms. It is implemented as a set of C programs and a number of python classes. It can be used as a standalone program, or the python classes can be directly imported by other applications.
EZ_Ages is an IDL code package that computes the mean, light-weighted stellar population age, [Fe/H], and abundance enhancements [Mg/Fe], [C/Fe], [N/Fe], and [Ca/Fe] for unresolved stellar populations. This is accomplished by comparing Lick index line strengths between the data and the stellar population models of Schiavon (2007), using a method described in Graves & Schiavon (2008). The algorithm uses the inversion of index-index model grids to determine ages and abundances, and exploits the sensitivities of the various Lick indices to measure Mg, C, N, and Ca enhancements over their solar abundances with respect to Fe.
In EyE (Enhance Your Extraction) an artificial neural network connected to pixels of a moving window (retina) is trained to associate these input stimuli to the corresponding response in one or several output image(s). The resulting filter can be loaded in SExtractor to operate complex, wildly non-linear filters on astronomical images. Typical applications of EyE include adaptive filtering, feature detection and cosmetic corrections.
Extreme-deconvolution is a general algorithm to infer a d-dimensional distribution function from a set of heterogeneous, noisy observations or samples. It is fast, flexible, and treats the data's individual uncertainties properly, to get the best description possible for the underlying distribution. It performs well over the full range of density estimation, from small data sets with only tens of samples per dimension, to large data sets with hundreds of thousands of data points.
ExtLaw_H18 generates the extinction law between 0.8 - 2.2 microns. The law is derived using the Westerlund 1 (Wd1) main sequence (A_Ks ~ 0.6 mag) and Arches cluster field Red Clump at the Galactic Center (A_Ks ~ 2.7 mag). To derive the law a Wd1 cluster age of 5 Myr is assumed, though changing the cluster age between 4 Myr -- 7 Myr has no effect on the law. This extinction law can be applied to highly reddened stellar populations that have similar foreground material as Wd1 and the Arches RC, namely dust from the spiral arms of the Milky Way in the Galactic Plane.
Extinction-distances uses the number of foreground stars and a Galactic model of the stellar distribution to estimate the distance to dark clouds. It exploits the relatively narrow range of intrinsic near-infrared colors of stars to separate foreground from background stars. An advantage of this method is that the distribution of stellar colors in the Galactic model need not be precisely correct, only the number density as a function of distance from the Sun.
The program EXTINCT.FOR is a FORTRAN subroutine summarizing a three-dimensional visual Galactic extinction model, based on a number of published studies. INPUTS: Galactic latitude (degrees), Galactic longitude (degrees), and source distance (kpc). OUTPUTS (magnitudes): Extinction, extinction error, a statistical correction term, and an array containing extinction and extinction error from each subroutine. The model is useful for correcting visual magnitudes of Galactic sources (particularly in statistical models), and has been used to find Galactic extinction of extragalactic sources. The model's limited angular resolution (subroutine-dependent, but with a minimum resolution of roughly 2 degrees) is necessitated by its ability to describe three-dimensional structure.
EXSdetect is a python implementation of an X-ray source detection algorithm which is optimally designed to detected faint extended sources and makes use of Voronoi tessellation and Friend-of-Friend technique. It is a flexible tool capable of detecting extended sources down to the lowest flux levels attainable within instrumental limitations while maintaining robust photometry, high completeness, and low contamination, regardless of source morphology. EXSdetect was developed mainly to exploit the ever-increasing wealth of archival X-ray data, but is also ideally suited to explore the scientific capabilities of future X-ray facilities, with a strong focus on investigations of distant groups and clusters of galaxies.
ExPRES (Exoplanetary and Planetary Radio Emission Simulator) reproduces the occurrence of CMI-generated radio emissions from planetary magnetospheres, exoplanets or star-planet interacting systems in time-frequency plane, with special attention given to computation of the radio emission beaming at and near its source. Physical information drawn from such radio observations may include the location and dynamics of the radio sources, the type of current system leading to electron acceleration and their energy and, for exoplanetary systems, the magnetic field strength, the orbital period of the emitting body and the rotation period, tilt and offset of the planetary magnetic field. Most of these parameters can be remotely measured only via radio observations. ExPRES code provides the proper framework of analysis and interpretation for past (Cassini, Voyager, Galileo), current (Juno, ground-based radio telescopes) and future (BepiColombo, Juice) observations of planetary radio emissions, as well as for future detection of radio emissions from exoplanetary systems.
The simple, straightforward Exotrending code detrends exoplanet transit light curves given a light curve (flux versus time) and good ephemeris (epoch of first transit and orbital period). The code has been tested with Kepler and K2 light curves and should work with any other light curve.
ExoSOFT provides orbital analysis of exoplanets and binary star systems. It fits any combination of astrometric and radial velocity data, and offers four parameter space exploration techniques, including MCMC. It is packaged with an automated set of post-processing and plotting routines to summarize results, and is suitable for performing orbital analysis during surveys with new radial velocity and direct imaging instruments.
EXOSIMS generates and analyzes end-to-end simulations of space-based exoplanet imaging missions. The software is built up of interconnecting modules describing different aspects of the mission, including the observatory, optical system, and scheduler (encoding mission rules) as well as the physical universe, including the assumed distribution of exoplanets and their physical and orbital properties. Each module has a prototype implementation that is inherited by specific implementations for different missions concepts, allowing for the simulation of widely variable missions.
Exorings is suitable for surveying entire catalogs of transiting planet candidates for exoring candidates, providing a subset of objects worthy of more detailed light curve analysis. Moreover, it is highly suited for uncovering evidence of a population of ringed planets by comparing the radius anomaly and PR-effects in ensemble studies.
Exorings, written in Python, contains tools for displaying and fitting giant extrasolar planet ring systems; it uses FITS formatted data for input.
ExoPriors calculates a log-likelihood penalty for an input set of transit parameters to account for observational bias (geometric and signal-to-noise ratio detection bias) of transiting exoplanets. Written in Python, the code calculates this log-likelihood penalty in one of seven user-specified cases specified with Boolean input parameters for geometric and/or SNR bias, grazing or non-grazing events, and occultation events.
Exopop is a general hierarchical probabilistic framework for making justified inferences about the population of exoplanets. Written in python, it requires that the occurrence rate density be a smooth function of period and radius (employing a Gaussian process) and takes survey completeness and observational uncertainties into account. Exopop produces more accurate estimates of the whole population than standard procedures based on weighting by inverse detection efficiency.
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