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Frechet sufficient dimension reduction for random objects

期刊: BIOMETRIKA, 2022; 109 (4)

We consider Frechet sufficient dimension reduction with responses being complex random objects in a metric space and high-dimensional Euclidean predic......

JIF:4.088

Stratification and optimal resampling for sequential Monte Carlo

期刊: BIOMETRIKA, 2022; 109 (1)

Sequential Monte Carlo algorithms are widely accepted as powerful computational tools for making inference with dynamical systems. A key step in seque......

JIF:4.088

Inverse moment methods for sufficient forecasting using high-dimensional predictors

期刊: BIOMETRIKA, 2022; 109 (2)

We consider forecasting a single time series using a large number of predictors in the presence of a possible nonlinear forecast function. Assuming th......

JIF:4.088

Dimension reduction for covariates in network data

期刊: BIOMETRIKA, 2022; 109 (1)

A problem of major interest in network data analysis is to explain the strength of connections using context information. To achieve this, we introduc......

JIF:4.088

An approximate randomization test for the high-dimensional two-sample Behrens-Fisher problem under arbitrary covariances

期刊: BIOMETRIKA, 2022; 109 (4)

This paper is concerned with the problem of comparing the population means of two groups of independent observations. An approximate randomization tes......

JIF:4.088

General ways to improve false coverage rate-adjusted selective confidence intervals

期刊: BIOMETRIKA, 2022; 109 (1)

Post-selection inference on thousands of parameters has attracted considerable research interest in recent years. Specifically, Benjamini & Yekuti......

JIF:4.088

Distributed inference for the extreme value index

期刊: BIOMETRIKA, 2022; 109 (1)

In this paper we investigate a divide-and-conquer algorithm for estimating the extreme value index when data are stored in multiple machines. The orac......

JIF:4.088

Integrated conditional moment test and beyond: when the number of covariates is divergent

期刊: BIOMETRIKA, 2022; 109 (1)

The classical integrated conditional moment test is a promising method for model checking and its basic idea has been applied to develop several varia......

JIF:4.088

Functional regression on the manifold with contamination

期刊: BIOMETRIKA, 2021; 108 (1)

We propose a new method for functional nonparametric regression with a predictor that resides on a finite-dimensional manifold, but is observable only......

Event history analysis of dynamic networks

期刊: BIOMETRIKA, 2021; 108 (1)

Statistical analysis on networks has received growing attention due to demand from various emerging applications. In dynamic networks, one of the key ......

Lattice-based designs with quasi-optimal separation distance on all projections

期刊: BIOMETRIKA, 2021; 108 (2)

Experimental designs that spread points apart from each other on projections are important for computer experiments, when not necessarily all factors ......

Heterogeneous individual risk modelling of recurrent events

期刊: BIOMETRIKA, 2021; 108 (1)

Progression of chronic disease is often manifested by repeated occurrences of disease-related events over time. Delineating the heterogeneity in the r......

Specification tests for covariance structures in high-dimensional statistical models

期刊: BIOMETRIKA, 2021; 108 (2)

We consider testing the covariance structure in statistical models. We focus on developing such tests when the random vectors of interest are not dire......

High-dimensional empirical likelihood inference

期刊: BIOMETRIKA, 2021; 108 (1)

High-dimensional statistical inference with general estimating equations is challenging and remains little explored. We study two problems in the area......

Diagnosing missing always at random in multivariate data

期刊: BIOMETRIKA, 2020; 107 (1)

Models for analysing multivariate datasets with missing values require strong, often unassessable, assumptions. The most common of these is that the m......

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