Related papers: Improving the Accuracy of Planet Occurrence Rates …

We present robust planet occurrence rates for Kepler planet candidates around M stars for planet radii $R_p = 0.5-4~\textrm{R}_\oplus$ and orbital periods $P = 0.5-256$ days using the approximate Bayesian computation (ABC) technique. This…

We present Kepler exoplanet occurrence rates inferred with approximate Bayesian computation (ABC). By using the same planet catalogue, stellar sample, and characterization of completeness and reliability as Bryson et al. (2020), we are able…

Approximate Bayesian computation (ABC) methods, which are applicable when the likelihood is difficult or impossible to calculate, are an active topic of current research. Most current ABC algorithms directly approximate the posterior…

Approximate Bayesian Computation (ABC) has become increasingly prominent as a method for conducting parameter inference in a range of challenging statistical problems, most notably those characterized by an intractable likelihood function.…

"Approximate Bayesian Computation" (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely…

Currently, we have only limited means to probe the presence of planets at large orbital separations. Foreman-Mackey et al. searched for long-period transiting planets in the Kepler light curves using an automated pipeline. Here, we apply…

We present here the first observationally based determination of the rate of occurrence of circumbinary planets. This is derived from the publicly available Kepler data, using an automated search algorithm and debiasing process to produce…

New transiting planet candidates are identified in sixteen months (May 2009 - September 2010) of data from the Kepler spacecraft. Nearly five thousand periodic transit-like signals are vetted against astrophysical and instrumental false…

We present a framework to conservatively estimate the probability that any particular planet-like transit signal observed by the Kepler mission is in fact a planet, prior to any ground-based follow-up efforts. We use Monte Carlo methods…

We characterize the occurrence rate of planets, ranging in size from 0.5-16 R$_\oplus$, orbiting FGK stars with orbital periods from 0.5-500 days. Our analysis is based on results from the "DR25" catalog of planet candidates produced by…

Approximate Bayesian Computation (ABC) methods are applicable to statistical models specified by generative processes with analytically intractable likelihoods. These methods try to approximate the posterior density of a model parameter by…

One core goal of the Kepler mission was to determine the frequency of Earth-like planets that orbit Sun-like stars. Accurately estimating this planet occurrence rate requires both a well-vetted list of planets and a clear understanding of…

Approximate Bayesian Computation (ABC for short) is a family of computational techniques which offer an almost automated solution in situations where evaluation of the posterior likelihood is computationally prohibitive, or whenever…

Bayesian inference is often used in cosmology and astrophysics to derive constraints on model parameters from observations. This approach relies on the ability to compute the likelihood of the data given a choice of model parameters. In…

Wide-field surveys for transiting planets, such as the NASA Kepler and TESS missions, are usually conducted without knowing which stars have binary companions. Unresolved and unrecognized binaries give rise to systematic errors in planet…

Approximate Bayesian Computation (ABC) enables statistical inference in simulator-based models whose likelihoods are difficult to calculate but easy to simulate from. ABC constructs a kernel-type approximation to the posterior distribution…

Unresolved stellar companions can cause both under-estimations in the radii of transiting planets and over-estimations of their detectability, affecting our ability to reliably measure planet occurrence rates. To quantify the latter, we…

Using the cumulative catalog of planets detected by the NASA Kepler mission, we reconstruct the intrinsic occurrence of Earth- to Neptune-size (1 - 4$R_{\oplus}$) planets and their distributions with radius and orbital period. We analyze…

Many modern statistical applications involve inference for complicated stochastic models for which the likelihood function is difficult or even impossible to calculate, and hence conventional likelihood-based inferential echniques cannot be…

Approximate Bayesian computation (ABC) is a likelihood-free approach for Bayesian inferences based on a rejection algorithm method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.…