ISSN 1932-6157 (print) ISSN 1941-7330 (online) THE ANNALS of APPLIED STATISTICS AN OFFICIAL JOURNAL OF THE INSTITUTE OF MATHEMATICAL STATISTICS Articles A Hermite–Gaussian based exoplanet radial velocity estimation method PARKER H. HOLZER,JESSI CISEWSKI-KEHE,DEBRA FISCHER AND LILY ZHAO 527 Hierarchical integrated spatial process modeling of monotone West Antarctic snow density curves. PHILIP A. WHITE,DURBAN G. KEELER AND SUMMER RUPPER 556 Estimating high-resolution Red Sea surface temperature hotspots, using a low-rank semiparametric spatial model. ARNAB HAZRA AND RAPHAËL HUSER 572 Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling..........TRYGVE OLAV FOSSUM,CÉDRIC TRAVELLETTI,JO EIDSVIK, DAV I D GINSBOURGER AND KANNA RAJAN 597 Aggregated pairwise classification of elastic planar shapes MIN HO CHO,SEBASTIAN KURTEK AND STEVEN N. 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ARCHIE AND FAN LI 747 Rapid design of metamaterials via multitarget Bayesian optimization YANG YANG,CHUNLIN JI AND KE DENG 768 A continuous-time semi-Markov model for animal movement in a dynamic environment DEVIN JOHNSON,NOEL PELLAND AND JEREMY STERLING 797 A Bayesian semiparametric Jolly–Seber model with individual heterogeneity: An application to migratory mallards at stopover . GUOHUI WU,SCOTT H. HOLAN, ALEXIS AVRIL AND JONAS WALDENSTRÖM 813 Inference of large modified Poisson-type graphical models: Application to RNA-seq data in childhood atopic asthma studies . .................RONG ZHANG,ZHAO REN, JUAN C. CELEDÓN AND WEI CHEN 831 Two-way sparsity for time-varying networks with applications in genomics THOMAS E. BARTLETT,IOANNIS KOSMIDIS AND RICARDO SILVA 856 continued Vol. 15, No. 2—June 2021 ISSN 1932-6157 (print) ISSN 1941-7330 (online) THE ANNALS of APPLIED STATISTICS AN OFFICIAL JOURNAL OF THE INSTITUTE OF MATHEMATICAL STATISTICS Articles—Continued from front cover A compositional model to assess expression changes from single-cell RNA-seq data XIUYU MA,KEEGAN KORTHAUER, CHRISTINA KENDZIORSKI AND MICHAEL A. NEWTON 880 Large-scale multiple inference of collective dependence with applications to protein function............ROBERT JERNIGAN,KEJUE JIA,ZHAO REN AND WEN ZHOU 902 A Bayesian nonparametric model for inferring subclonal populations from structured DNAsequencingdata................................SHAI HE,AARON SCHEIN, VISHAL SARSANI AND PATRICK FLAHERTY 925 Prediction of the NASH through penalized mixture of logistic regression models MARIE MORVAN,EMILIE DEVIJVER, MADISON GIACOFCI AND VALÉRIE MONBET 952 Efficient Bayesian inference of general Gaussian models on large phylogenetic trees PAUL BASTIDE,LAM SI TUNG HO,GUY BAELE, PHILIPPE LEMEY AND MARC A. SUCHARD 971 A covariance-enhanced approach to multitissue joint eQTL mapping with application to transcriptome-wideassociationstudies......................AARON J. MOLSTAD, WEI SUN AND LI HSU 998 Tensor-variate finite mixture modeling for the analysis of university professor remuneration..........................................SHUCHISMITA SARKAR, VOLODYMYR MELNYKOV AND XUWEN ZHU 1017 Inflection points in community-level homeless rates CHRIS GLYNN,THOMAS H. BYRNE AND DENNIS P. C ULHANE 1037 Length-biased semicompeting risks models for cross-sectional data: An application to currentdurationofpregnancyattemptdata..............ALEXANDER C. MCLAIN, SIYUAN GUO,MARIE THOMA AND JIAJIA ZHANG 1054 A bridging model to reconcile statistics based on data from multiple surveys ANDREEA L. ERCIULESCU,JEAN D. OPSOMER AND F. JAY BREIDT 1068 Vol. 15, No. 2—June 2021 THE ANNALS OF APPLIED STATISTICS Vol. 15, No. 2, pp. 527–1079 June 2021 INSTITUTE OF MATHEMATICAL STATISTICS (Organized September 12, 1935) The purpose of the Institute is to foster the development and dissemination of the theory and applications of statistics and probability. 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Editor: Vlada Limic, UMR 7501 de l’Université de Strasbourg et du CNRS, 7 rue René Descartes, 67084 Strasbourg Cedex, France The Annals of Applied Statistics [ISSN 1932-6157 (print); ISSN 1941-7330 (online)], Volume 15, Number 2, June 2021. Published quarterly by the Institute of Mathematical Statistics, 9760 Smith Road, Waite Hill, Ohio 44094, USA. Periodicals postage pending at Cleveland, Ohio, and at additional mailing offices. POSTMASTER: Send address changes to The Annals of Applied Statistics, Institute of Mathematical Statistics, Dues and Subscriptions Office, PO Box 729, Middletown, Maryland 21769, USA. Copyright © 2021 by the Institute of Mathematical Statistics Printed in the United States of America The Annals of Applied Statistics 2021, Vol. 15, No. 2, 527–555 https://doi.org/10.1214/20-AOAS1406 © Institute of Mathematical Statistics, 2021 A HERMITE–GAUSSIAN BASED EXOPLANET RADIAL VELOCITY ESTIMATION METHOD BY PARKER H. HOLZER1,JESSI CISEWSKI-KEHE2,DEBRA FISCHER3,* AND LILY ZHAO3,† 1Department of Statistics and Data Science, Yale University, [email protected] 2Department of Statistics, University of Wisconsin–Madison, [email protected] 3Department of Astronomy, Yale University, *debra.fi[email protected]; †[email protected] As the first successful technique used to detect exoplanets orbiting dis- tant stars, the radial velocity method aims to detect a periodic Doppler shift in a stellar spectrum due to the star’s motion along the line sight. We intro- duce a new, mathematically rigorous approach to detect such a signal that accounts for the smooth functional relationship of neighboring wavelengths in the spectrum, minimizes the role of wavelength interpolation, accounts for heteroskedastic noise and easily allows for accurate calculation of the esti- mated radial velocity standard error. Using Hermite–Gaussian functions, we show that the problem of detecting a Doppler shift in the spectrum can be re- duced to linear regression in many settings. A simulation study demonstrates that the proposed method is able to accurately estimate an individual spec- − trum’s radial velocity with precision below 0.3ms 1, corresponding to a Doppler shift much smaller than the size of a spectral pixel. Furthermore, the new method outperforms the traditional cross-correlation function approach for estimating the radial velocity by reducing the root mean squared error − up to 15 cm s 1. The proposed method is also demonstrated on a new set of observations from the EXtreme PREcision Spectrometer (EXPRES) for the host star 51 Pegasi, and successfully recovers estimates of the planetary companion’s parameters that agree well with previous studies. The method is implemented in the R package rvmethod, and supplemental Python code is also available. REFERENCES ANGLADA-ESCUDÉ,G.andBUTLER, R. P. (2012). The harps-terra project. I. Description of the algorithms, performance, and new measurements on a few remarkable stars observed by harps. Astrophys. J., Suppl. Ser. 200