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Parametrizing the Kepler exoplanet period-radius distribution with the bivariate normal inverse Gaussian distribution
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Parametrizing the Kepler exoplanet period-radius distribution with the bivariate normal inverse Gaussian distribution

Jen-Hao ChenWen-Liang Hung
Journal of Applied Statistics, 卷.46(4)
2019

摘要

GK-type star;Kepler planets;normal inverse Gaussian distribution;occurrence rate;particle swarm optimization Statistics and Probability Statistics Probability and Uncertainty
This paper presents a simple and robust method for obtaining a comprehensive understanding of the joint period and radius distribution in Kepler exoplanets. The proposed method is based on particle swarm optimization and bivariate Normal Inverse Gaussian distribution. Furthermore, in the construction of the probability density function, this study selects planet-host stars with the GK-type. The injecting approach is also employed to solve the survey completeness of sample. The resulting occurrence rate of Earth analogs is 0.025 with a 95% bootstrap confidence interval between 0.023 and 0.032.

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