Résultats de recherche pour « Survey Sampling »

We use observations from the 9 square degree multiwavelength survey in Bootes to identify hundreds of obscured active galactic nuclei (AGN) with high redshifts (z > 0.7), luminosities (L_bol > 10^45 ergs/s), and moderate obscuring columns (N_H > 10^22 cm^-2), and to measure the clustering properties of X-ray AGN at z > 1. In the Bootes region, shallow (5 ks) Chandra X-ray observations have detected ~4,000 X-ray sources, and the same region has been mapped with deep optical imaging and by Spitzer IRAC, which detects ~300,000 point sources, of which ~30,000 have detections in all four IRAC bands, for which we can select AGN on the basis of their mid-IR colors. With the MMT/Hectospec we have obtained modest resolution optical spectra for about half the X-ray sources (out to z > 3) and ~20,000 galaxies (out to z = 0.7). With this multiwavelength data we select >400 AGN per square degree (compared to 12 per square degree from SDSS). Among a sample of IRAC-selected AGN we identify 641 candidate obscured objects based on their R band and IRAC luminosities. We use X-ray stacking techniques to verify that they are obscured AGN and measure their absorbing column densities. We also measure the three-dimensional two-point correlation function for X-ray selected AGN.

The twentieth century saw a dramatic change in the way information was generated as probability sampling replaced full enumeration.We examine some key events of the past and issues being addressed today to gain perspective on the requirements that might steer changes in the direction of survey sampling in the future.The potential for online Web panels and other methods that do not use probability sampling are considered.Finally, we conclude with some thoughts on how the future of survey sampling might be shaped by unpredictable factors.Contemplating the potential directions that survey sampling may take in the future requires considering the current state of affairs and how we arrived at this point.Despite occasional issues and controversies, it seems fair to say that survey sampling, and probability sampling in particular, has helped transform our view of society and the issues it faces.Perhaps even more importantly, sampling has changed how we think about obtaining information from a large population.We have seen the transition from full enumeration as the only acceptable method of learning about a population that was the standard in the late nineteenth century to ''partial investigations'' and finally to a full theory of sampling.Kruskal and Mosteller (1980) describe this transformation.This change has made it possible to study a wide range of topics about our society in a cost-effective and timely manner.The findings from surveys are generally accepted in popular, legal, and technical areas, although there are still debates about methods of implementation.Election surveys, both those in the run-up to the election and exit polls, demonstrate both the general acceptance and concerns about methods.Election surveys are very public and their accuracy is easily judged; the results of these surveys are highly reported and the

The recent development and wider accessibility of LLMs have spurred discussions about how they can be used in survey research, including classifying open-ended survey responses. Due to their linguistic capacities, it is possible that LLMs are an efficient alternative to time-consuming manual coding and the pre-training of supervised machine learning models. As most existing research on this topic has focused on English-language responses relating to non-complex topics or on single LLMs, it is unclear whether its findings generalize and how the quality of these classifications compares to established methods. In this study, we investigate to what extent different LLMs can be used to code open-ended survey responses in other contexts, using German data on reasons for survey participation as an example. We compare several state-of-the-art LLMs and several prompting approaches, and evaluate the LLMs' performance by using human expert codings. Overall performance differs greatly between LLMs, and only a fine-tuned LLM achieves satisfactory levels of predictive performance. Performance differences between prompting approaches are conditional on the LLM used. Finally, LLMs' unequal classification performance across different categories of reasons for survey participation results in different categorical distributions when not using fine-tuning. We discuss the implications of these findings, both for methodological research on coding open-ended responses and for their substantive analysis, and for practitioners processing or substantively analyzing such data. Finally, we highlight the many trade-offs researchers need to consider when choosing automated methods for open-ended response classification in the age of LLMs. In doing so, our study contributes to the growing body of research about the conditions under which LLMs can be efficiently, accurately, and reliably leveraged in survey research.

A purpose built 7-beam methanol receiver, installed on the Parkes Radio Telescope, was used to survey the Galactic plane for newly forming high mass stars, pinpointed by strong methanol maser emission at 6.7 GHz. The Methanol Multibeam (MMB) survey observed over 60% of the Galactic plane, detecting close to 1000 sources. The MMB survey provides a huge resource for studies of high-mass star formation, an important stage in the evolution of the interstellar medium. The MMB survey is also a valuable resource for investigations into the structure and dynamics of our Galaxy: with narrow velocity ranges of emission (typically only a few km/s) and velocities closely correlated with the systemic velocity of their surrounding molecular clouds, 6.7-GHz methanol masers provide estimates of the spiral arm velocities and their structure. I will discuss the techniques and properties of the MMB survey, before outlining recent results, which include the identification of regions of enhanced star formation believed to be indicative of the origins of the spiral arms and the interaction of the Galactic bar with the 3-kpc arms. I will also discuss the various follow-up programmes including a study of magnetic fields through associated hydroxyl masers.

Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Small-area estimation.

We make the first data release (DR1) of the ongoing ESO Public Survey SAMPLING (http://dx.doi.org/10.7910/DVN/0L8NHX). DR1 comprises of 124 fields distributed in $70^\circ < l < 216^\circ$, $-35^\circ < b < 25^\circ$. The 12CO and 13CO (2-1) cubes are gridded in $8"$ pixels, with an effective resolution of $36"$. The channel width is 0.33 km/s and the RMS noise is $T_{\rm mb}<0.2$ K. Once completed, SAMPLING and complementary surveys will initiate the first major step forward to characterize molecular clouds and star formation on truly Galactic scales.

Summary Calibration estimation, where the sampling weights are adjusted to make certain estimators match known population totals, is commonly used in survey sampling. The generalized regression estimator is an example of a calibration estimator. Given the functional form of the calibration adjustment term, we establish the asymptotic equivalence between the functional‐form calibration estimator and an instrumental variable calibration estimator where the instrumental variable is directly determined from the functional form in the calibration equation. Variance estimation based on linearization is discussed and applied to some recently proposed calibration estimators. The results are extended to the estimator that is a solution to the calibrated estimating equation. Results from a limited simulation study are presented.

We describe the Dark Energy Survey (DES), a proposed optical-near infrared survey of 5000 sq. deg of the South Galactic Cap to ~24th magnitude in SDSS griz, that would use a new 3 sq. deg CCD camera to be mounted on the Blanco 4-m telescope at Cerro Telolo Inter-American Observatory (CTIO). The survey data will allow us to measure the dark energy and dark matter densities and the dark energy equation of state through four independent methods: galaxy clusters, weak gravitational lensing tomography, galaxy angular clustering, and supernova distances. These methods are doubly complementary: they constrain different combinations of cosmological model parameters and are subject to different systematic errors. By deriving the four sets of measurements from the same data set with a common analysis framework, we will obtain important cross checks of the systematic errors and thereby make a substantial and robust advance in the precision of dark energy measurements.