Statistics

Authors and titles for May 2020

[201] arXiv:2005.07314 [pdf, other]

Title: Hierarchical causal variance decomposition for institution and provider comparisons in healthcare

Bo Chen, Olli Saarela

Journal-ref: Health Services and Outcomes Research Methodology (2023)

Subjects: Methodology (stat.ME)

[202] arXiv:2005.07322 [pdf, other]

Title: Instrumental variable estimation of early treatment effect in randomized screening trials

Sudipta Saha, Zhihui Liu, Olli Saarela

Comments: Lifetime Data Anal (2021)

Subjects: Methodology (stat.ME)

[203] arXiv:2005.07334 [pdf, other]

Title: Optimizing SAR data processing and thresholding for forest change detection: an application for early deforestation warnings on eastern Amazonia

Juan Doblas

Comments: To be published on the XX SBSR (2021)

Subjects: Applications (stat.AP); Image and Video Processing (eess.IV)

[204] arXiv:2005.07342 [pdf, other]

Title: Model Linkage Selection for Cooperative Learning

Jiaying Zhou, Jie Ding, Kean Ming Tan, Vahid Tarokh

Subjects: Methodology (stat.ME); Machine Learning (stat.ML)

[205] arXiv:2005.07380 [pdf, other]

Title: Bayesian model inversion using stochastic spectral embedding

P.-R. Wagner, S. Marelli, B. Sudret

Journal-ref: Journal of Computational Physics, Vol. 436, 110141 (2021)

Subjects: Computation (stat.CO); Methodology (stat.ME)

[206] arXiv:2005.07397 [pdf, other]

Title: Contrast estimation of general locally stationary processes using coupling

J.-M. Bardet, P. Doukhan, O. Wintenberger

Comments: 42 pages, 13 figures

Subjects: Statistics Theory (math.ST)

[207] arXiv:2005.07402 [pdf, other]

Title: Stopping criterion for active learning based on deterministic generalization bounds

Hideaki Ishibashi, Hideitsu Hino

Comments: Accepted for publication at AISTATS 2020

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[208] arXiv:2005.07430 [pdf, other]

Title: Fast and Accurate Variational Inference for Models with Many Latent Variables

Rubén Loaiza-Maya, Michael Stanley Smith, David J. Nott, Peter J. Danaher

Comments: Macroeconomic example was replaced by the bigger and more challenging time varying parameter vector autoregression model with stochastic volatility. Microeconomic example was extended to 20,000 individuals and variational subsampling is also implemented for this example. Small microeconomics example now uses 1000 individuals

Subjects: Methodology (stat.ME); Econometrics (econ.EM)

[209] arXiv:2005.07450 [pdf, other]

Title: What is resolution? A statistical minimax testing perspective on super-resolution microscopy

Gytis Kulaitis, Axel Munk, Frank Werner

Subjects: Statistics Theory (math.ST); Applications (stat.AP)

[210] arXiv:2005.07452 [pdf, other]

Title: Nowcasting fatal COVID-19 infections on a regional level in Germany

Marc Schneble, Giacomo De Nicola, Göran Kauermann, Ursula Berger

Comments: 22 pages, 9 Figures

Subjects: Applications (stat.AP); Populations and Evolution (q-bio.PE)

[211] arXiv:2005.07468 [pdf, other]

Title: Hierarchical Bayesian state-space modeling of age- and sex-structured wildlife population dynamics

Sabyasachi Mukhopadhyay, Hans-Peter Piepho, Sourabh Bhattacharya, Holly T. Dublin, Joseph O. Ogutu

Subjects: Applications (stat.AP)

[212] arXiv:2005.07484 [pdf, other]

Title: Evaluating methods for Lasso selective inference in biomedical research by a comparative simulation study

Michael Kammer, Daniela Dunkler, Stefan Michiels, Georg Heinze

Comments: 42 pages, 19 figures, 7 tables

Subjects: Methodology (stat.ME)

[213] arXiv:2005.07568 [pdf, other]

Title: Graphical modeling of stochastic processes driven by correlated errors

Søren Wengel Mogensen, Niels Richard Hansen

Comments: 43 pages

Journal-ref: Bernoulli (2022), Vol. 28, No. 4, 3023-3050

Subjects: Statistics Theory (math.ST)

[214] arXiv:2005.07573 [pdf, other]

Title: Analysis and Simulation of Extremes and Rare Events in Complex Systems

Meagan Carney, Holger Kantz, Matthew Nicol

Comments: 32 pages, 16 figures

Subjects: Methodology (stat.ME)

[215] arXiv:2005.07587 [pdf, other]

Title: Non-Sparse PCA in High Dimensions via Cone Projected Power Iteration

Yufei Yi, Matey Neykov

Subjects: Statistics Theory (math.ST); Computation (stat.CO); Methodology (stat.ME); Machine Learning (stat.ML)

[216] arXiv:2005.07605 [pdf, other]

Title: On Learnability under General Stochastic Processes

A. Philip Dawid, Ambuj Tewari

Comments: The regression results in the previous version have been made stronger

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[217] arXiv:2005.07674 [pdf, other]

Title: Power laws distributions in objective priors

Pedro L. Ramos, Francisco A. Rodrigues, Eduardo Ramos, Dipak K. Dey, Francisco Louzada

Subjects: Statistics Theory (math.ST)

[218] arXiv:2005.07742 [pdf, other]

Title: SEAM methodology for context-rich player matchup evaluations

Julia Wapner, David Dalpiaz, Daniel J. Eck

Subjects: Applications (stat.AP); Methodology (stat.ME)

[219] arXiv:2005.07804 [pdf, other]

Title: High-dimensional Bayesian Optimization of Personalized Cardiac Model Parameters via an Embedded Generative Model

Jwala Dhamala, Sandesh Ghimire, John L. Sapp, B. Milan Horácek, Linwei Wang

Comments: MICCAI 2018

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Optimization and Control (math.OC)

[220] arXiv:2005.07844 [pdf, other]

Title: Nonasymptotic Laplace approximation under model misspecification

Anirban Bhattacharya, Debdeep Pati

Comments: 23 pages. Fixed minor technical glitches in the proof of Theorem 2 in the updated version

Subjects: Statistics Theory (math.ST)

[221] arXiv:2005.07852 [pdf, other]

Title: Geodesics in fibered latent spaces: A geometric approach to learning correspondences between conditions

Tariq Daouda, Reda Chhaibi, Prudencio Tossou, Alexandra-Chloé Villani

Comments: 36 pages, many figures. v1: Preliminary version. v2: Minor ref fix. v3: Submitted version with enhanced presentation

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Differential Geometry (math.DG); Genomics (q-bio.GN)

[222] arXiv:2005.07866 [pdf, other]

Title: Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data

Deepesh Data, Suhas Diggavi

Comments: 57 pages, 2 figures

Subjects: Machine Learning (stat.ML); Cryptography and Security (cs.CR); Distributed, Parallel, and Cluster Computing (cs.DC); Machine Learning (cs.LG)

[223] arXiv:2005.07882 [pdf, other]

Title: Curating a COVID-19 data repository and forecasting county-level death counts in the United States

Nick Altieri, Rebecca L. Barter, James Duncan, Raaz Dwivedi, Karl Kumbier, Xiao Li, Robert Netzorg, Briton Park, Chandan Singh, Yan Shuo Tan, Tiffany Tang, Yu Wang, Chao Zhang, Bin Yu

Comments: Authors ordered alphabetically. All authors contributed significantly to this work. All collected data, modeling code, forecasts, and visualizations are updated daily and available at \url{this https URL}

Journal-ref: Published in Harvard Data Science Review, 2020

Subjects: Applications (stat.AP); Machine Learning (cs.LG)

[224] arXiv:2005.07927 [pdf, other]

Title: BART-based inference for Poisson processes

Stamatina Lamprinakou, Mauricio Barahona, Seth Flaxman, Sarah Filippi, Axel Gandy, Emma McCoy

Comments: Accepted version including Supplementary Material. To appear in Computational Statistics & Data Analysis (CSDA)

Subjects: Statistics Theory (math.ST); Machine Learning (cs.LG)

[225] arXiv:2005.07938 [pdf, other]

Title: Efficient quantization and weak covering of high dimensional cubes

Jack Noonan, Anatoly Zhigljavsky

Subjects: Statistics Theory (math.ST)

[226] arXiv:2005.07939 [pdf, other]

Title: Predicting into unknown space? Estimating the area of applicability of spatial prediction models

Hanna Meyer, Edzer Pebesma

Comments: 16 pages, 10 figures, to be submitted to Methods in Ecology and Evolution

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[227] arXiv:2005.07946 [pdf, other]

Title: Transforming variables to central normality

Jakob Raymaekers, Peter J. Rousseeuw

Journal-ref: Machine Learning, 2021

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[228] arXiv:2005.08005 [pdf, other]

Title: Forecasting electricity prices with machine learning: Predictor sensitivity

Christof Naumzik, Stefan Feuerriegel

Subjects: Applications (stat.AP)

[229] arXiv:2005.08057 [pdf, other]

Title: Nested Model Averaging on Solution Path for High-dimensional Linear Regression

Yang Feng, Qingfeng Liu

Comments: 17 pages, 3 figures

Subjects: Methodology (stat.ME); Machine Learning (cs.LG); Econometrics (econ.EM); Computation (stat.CO); Machine Learning (stat.ML)

[230] arXiv:2005.08136 [pdf, other]

Title: Truncated Simulation and Inference in Edge-Exchangeable Networks

Xinglong Li, Trevor Campbell

Subjects: Statistics Theory (math.ST)

[231] arXiv:2005.08140 [pdf, other]

Title: Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes

Sebastian W. Ober, Laurence Aitchison

Comments: Accepted for publication at the 38th International Conference on Machine Learning (ICML 2021, PMLR 139), 33 pages

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[232] arXiv:2005.08155 [pdf, other]

Title: On loss functions and regret bounds for multi-category classification

Zhiqiang Tan, Xinwei Zhang

Subjects: Statistics Theory (math.ST); Methodology (stat.ME)

[233] arXiv:2005.08159 [pdf, other]

Title: Hamiltonian Assisted Metropolis Sampling

Zexi Song, Zhiqiang Tan

Subjects: Computation (stat.CO)

[234] arXiv:2005.08195 [pdf, other]

Title: Posterior properties of the Weibull distribution for censored data

Eduardo Ramos, Pedro L. Ramos

Subjects: Statistics Theory (math.ST)

[235] arXiv:2005.08217 [pdf, other]

Title: Robust subset selection

Ryan Thompson

Comments: To appear in Computational Statistics & Data Analysis

Subjects: Methodology (stat.ME)

[236] arXiv:2005.08261 [pdf, other]

Title: Latent Space Models for Dynamic Networks with Weighted Edges

Daniel K. Sewell, Yuguo Chen

Journal-ref: Social Networks, 44:105-116, 2016

Subjects: Methodology (stat.ME)

[237] arXiv:2005.08267 [pdf, other]

Title: Model-Based Longitudinal Clustering with Varying Cluster Assignments

Daniel K. Sewell, Yuguo Chen, William Bernhard, Tracy Sulkin

Journal-ref: Statistica Sinica. Vol. 26, No. 1 (January 2016), pp. 205-233

Subjects: Methodology (stat.ME)

[238] arXiv:2005.08269 [pdf, other]

Title: Analysis of the Formation of the Structure of Social Networks using Latent Space Models for Ranked Dynamic Networks

Daniel K. Sewell, Yuguo Chen

Journal-ref: J. R. Stat. Soc. C, 64: 611-633 (2015)

Subjects: Methodology (stat.ME)

[239] arXiv:2005.08276 [pdf, other]

Title: Latent Space Approaches to Community Detection in Dynamic Networks

Daniel K. Sewell, Yuguo Chen

Journal-ref: Bayesian Anal. 12 (2017), no. 2, 351--377. https://projecteuclid.org/euclid.ba/1461603847

Subjects: Methodology (stat.ME)

[240] arXiv:2005.08334 [pdf, other]

Title: Marginal likelihood computation for model selection and hypothesis testing: an extensive review

Fernando Llorente, Luca Martino, David Delgado, Javier Lopez-Santiago

Comments: Keywords: Marginal likelihood, Bayesian evidence, numerical integration, model selection, hypothesis testing, quadrature rules, double-intractable posteriors, partition functions

Journal-ref: SIAM Review, 2022

Subjects: Computation (stat.CO); Machine Learning (cs.LG)

[241] arXiv:2005.08361 [pdf, other]

Title: Bayesian biclustering for microbial metagenomic sequencing data via multinomial matrix factorization

Fangting Zhou, Kejun He, Qiwei Li, Robert S. Chapkin, Yang Ni

Subjects: Methodology (stat.ME)

[242] arXiv:2005.08373 [pdf, other]

Title: A Tutorial on Multivariate $k$-Statistics and their Computation

Kevin D. Smith

Subjects: Methodology (stat.ME); Statistics Theory (math.ST); Computation (stat.CO)

[243] arXiv:2005.08414 [pdf, other]

Title: Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs

Takashi Goda, Tomohiko Hironaka, Wataru Kitade, Adam Foster

Comments: major revision, 26 pages, 6 figures

Journal-ref: SIAM Journal on Scientific Computing, Volume 44, Issue 1, A286-A311, 2022

Subjects: Computation (stat.CO); Numerical Analysis (math.NA); Machine Learning (stat.ML)

[244] arXiv:2005.08415 [pdf, other]

Title: Selective Confidence Intervals for Martingale Regression Model

Ka Wai Tsang, Wei Dai

Subjects: Statistics Theory (math.ST); Other Statistics (stat.OT)

[245] arXiv:2005.08457 [pdf, other]

Title: Simultaneous Differential Network Analysis and Classification for High-dimensional Matrix-variate Data, with application to Brain Connectivity Alteration Detection and fMRI-guided Medical Diagnoses of Alzheimer's Disease

Chen Hao, Guo Ying, He Yong, Ji Jiadong, Liu Lei, Shi Yufeng, Wang Yikai, Yu Long, Zhang Xinsheng (for the Alzheimer's Disease Neuroimaging Initiative)

Subjects: Methodology (stat.ME)

[246] arXiv:2005.08459 [pdf, other]

Title: Bayesian adjustment for preferential testing in estimating the COVID-19 infection fatality rate

Harlan Campbell, Perry de Valpine, Lauren Maxwell, Valentijn MT de Jong, Thomas Debray, Thomas Jänisch, Paul Gustafson

Comments: 53 pages, 14 figures

Subjects: Methodology (stat.ME); Applications (stat.AP)

[247] arXiv:2005.08467 [pdf, other]

Title: Deep Latent-Variable Kernel Learning

Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

Comments: 13 pages, 8 figures, preprint under review

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[248] arXiv:2005.08482 [pdf, other]

Title: Variational Hyper-Encoding Networks

Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh

Comments: Accepted ECML-2021

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[249] arXiv:2005.08531 [pdf, other]

Title: Meta-learning with Stochastic Linear Bandits

Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[250] arXiv:2005.08543 [pdf, other]

Title: Necessary and sufficient conditions for causal feature selection in time series with latent common causes

Atalanti A. Mastakouri, Bernhard Schölkopf, Dominik Janzing

Subjects: Methodology (stat.ME); Machine Learning (stat.ML)