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Deconvolution Estimation of Onset of Pregnancy with Replicate Observations
Authors:Fabienne Comte  Adeline Samson  Julien J Stirnemann
Institution:1. MAP5, UMR CNRS 8145, Université Paris Descartes, Sorbonne Paris Cité;2. Obstetrics and Maternal ‐ Fetal Medicine, GHU Necker‐Enfants Malades, Université Paris Descartes
Abstract:In general, the precise date of onset of pregnancy is unknown and may only be estimated from ultrasound biometric measurements of the embryo. We want to estimate the density of the random variables corresponding to the interval between last menstrual period and true onset of pregnancy. The observations correspond to the variables of interest up to an additive noise. We suggest an estimation procedure based on deconvolution. It requires the knowledge of the density of the noise which is not available. But we have at our disposal another specific sample with replicate observations for twin pregnancies. This allows both to estimate the noise density and to improve the deconvolution step. Convergence rates of the final estimator are studied and compared with other settings. Our estimator involves a cut‐off parameter for which we propose a cross‐validation type procedure. Lastly, we estimate the target density in spontaneous pregnancies with an estimation of the noise obtained from replicate observations in twin pregnancies.
Keywords:deconvolution  density estimation  non‐parametric methods  dating of pregnancy  mean square risk  replicate observations
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