Related papers: Improving the Accuracy of Planet Occurrence Rates …
Approximate Bayesian computation (ABC) is a simulation-based likelihood-free method applicable to both model selection and parameter estimation. ABC parameter estimation requires the ability to forward simulate datasets from a candidate…
Approximate Bayesian computation (ABC) is a set of techniques for Bayesian inference when the likelihood is intractable but sampling from the model is possible. This work presents a simple yet effective ABC algorithm based on the…
We infer the period ($P$) and size ($R_p$) distribution of Kepler transiting planet candidates with $R_p\ge 1 R_{\rm Earth}$ and $P < 250$ days hosted by solar-type stars. The planet detection efficiency is computed by using measured noise…
Binary stars are ubiquitous; the majority of solar-type stars exist in binaries. Exoplanet occurrence rate is suppressed in binaries, but some multiples do still host planets. Binaries cause observational biases in planet parameters, with…
We propose a novel approach to approximate Bayesian computation (ABC) that seeks to cater for possible misspecification of the assumed model. This new approach can be equally applied to rejection-based ABC and to popular regression…
Approximate Bayesian computation performs approximate inference for models where likelihood computations are expensive or impossible. Instead simulations from the model are performed for various parameter values and accepted if they are…
Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data. Approximate Bayesian Computation (ABC) is devoted to these complex…
We analyze data from the Quarter 1-17 Data Release 24 (Q1--Q17 DR24) planet candidate catalog from NASA's Kepler mission, specifically comparing systems with single transiting planets to systems with multiple transiting planets, and…
We re-determine planetary occurrences around M dwarfs using 20 years of observations from HARPS on 197 targets. The first aim of this study is to propose more precise occurrence rates using the large volume of the sample but also variations…
Understanding the occurrence of Earth-sized planets in the habitable zone of Sun-like stars is essential to the search for Earth analogues. Yet a lack of reliable Kepler detections for such planets has forced many estimates to be derived…
Jupiter-mass planets with large semi-major axes ($a > 1.0$ AU) occur at a higher rate around evolved intermediate mass stars. There is a pronounced paucity of close-in ($a < 0.6$ AU), intermediate period ($5 < P < 100$ days), low-mass…
NASA's Kepler Space Telescope was designed to determine the frequency of Earth-sized planets orbiting Sun-like stars, but these planets are on the very edge of the mission's detection sensitivity. Accurately determining the occurrence rate…
Many scientifically well-motivated statistical models in natural, engineering, and environmental sciences are specified through a generative process. However, in some cases, it may not be possible to write down the likelihood for these…
Many models of interest in the natural and social sciences have no closed-form likelihood function, which means that they cannot be treated using the usual techniques of statistical inference. In the case where such models can be…
Many statistical models can be simulated forwards but have intractable likelihoods. Approximate Bayesian Computation (ABC) methods are used to infer properties of these models from data. Traditionally these methods approximate the posterior…
In many inference problems, the evaluation of complex and costly models is often required. In this context, Bayesian methods have become very popular in several fields over the last years, in order to obtain parameter inversion, model…
In order to gain a better understanding of planet formation and evolution, it is important to examine the statistics of exoplanets in the Galactic context. By combining information on stellar elemental abundances and kinematics, we…
We introduce a new method to infer the posterior distribution for planet occurrence rates from radial-velocity (RV) observations. The approach combines posterior samples from the analysis of individual RV datasets of several stars, using…
Simulation models for pedestrian crowds are a ubiquitous tool in research and industry. It is crucial that the parameters of these models are calibrated carefully and ultimately it will be of interest to compare competing models to decide…
The most abundant stars in the Galaxy, M dwarfs, are very commonly hosts to diverse systems of low-mass planets. Their abundancy implies that the general occurrence rate of planets is dominated by their occurrence rate around such M dwarfs.…