Search Results - "Biometrika"

Quasi-oracle estimation of heterogeneous treatment effects by Nie, X, Wager, S

“…Summary Flexible estimation of heterogeneous treatment effects lies at the heart of many statistical applications, such as personalized medicine and optimal…”
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A useful variant of the Davis—Kahan theorem for statisticians by YU, Y., WANG, T., SAMWORTH, R. J.

“…The Davis—Kahan theorem is used in the analysis of many statistical procedures to bound the distance between subspaces spanned by population eigenvectors and…”
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Combining p -values via averaging by Vovk, Vladimir, Wang, Ruodu

“…Summary This paper proposes general methods for the problem of multiple testing of a single hypothesis, with a standard goal of combining a number of…”
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Identifying causal effects with proxy variables of an unmeasured confounder by MIAO, WANG, GENG, ZHI, TCHETGEN TCHETGEN, ERIC J.

“…We consider a causal effect that is confounded by an unobserved variable, but for which observed proxy variables of the confounder are available. We show that…”
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Multivariate output analysis for Markov chain Monte Carlo by Vats, Dootika, Flegal, James M, Jones, Galin L

“…SUMMARY Markov chain Monte Carlo produces a correlated sample which may be used for estimating expectations with respect to a target distribution. A…”
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Nonparametric independence testing via mutual information by Berrett, T B, Samworth, R J

“…Summary We propose a test of independence of two multivariate random vectors, given a sample from the underlying population. Our approach is based on the…”
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General Bayesian updating and the loss-likelihood bootstrap by Lyddon, S P, Holmes, C C, Walker, S G

“…Summary In this paper we revisit the weighted likelihood bootstrap, a method that generates samples from an approximate Bayesian posterior of a parametric…”
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Network cross-validation by edge sampling by Li, Tianxi, Levina, Elizaveta, Zhu, Ji

“…Summary While many statistical models and methods are now available for network analysis, resampling of network data remains a challenging problem…”
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Maximum projection designs for computer experiments by JOSEPH, V. ROSHAN, GUL, EVREN, BA, SHAN

“…Space-filling properties are important in designing computer experiments. The traditional maximin and minimax distance designs consider only space-filling in…”
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Optimal subsampling for quantile regression in big data by Wang, Haiying, Ma, Yanyuan

“…Summary We investigate optimal subsampling for quantile regression. We derive the asymptotic distribution of a general subsampling estimator and then derive…”
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Identifiability of Gaussian structural equation models with equal error variances by PETERS, J., BÜHLMANN, P.

“…We consider structural equation models in which variables can be written as a function of their parents and noise terms, which are assumed to be jointly…”
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Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models by Kosmidis, Ioannis, Firth, David

“…Summary Penalization of the likelihood by Jeffreys’ invariant prior, or a positive power thereof, is shown to produce finite-valued maximum penalized…”
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Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations by Wang, Yixin, Zubizarreta, Jose R

“…Summary Weighting methods are widely used to adjust for covariates in observational studies, sample surveys, and regression settings. In this paper, we study a…”
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Robust estimation of causal effects via a high-dimensional covariate balancing propensity score by Ning, Yang, Sida, Peng, Imai, Kosuke

“…Summary We propose a robust method to estimate the average treatment effects in observational studies when the number of potential confounders is possibly much…”
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Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator by DOUCET, A., PITT, M. K., DELIGIANNIDIS, G., KOHN, R.

“…When an unbiased estimator of the likelihood is used within a Metropolis—Hastings chain, it is necessary to trade off the number of Monte Carlo samples used to…”
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Doubly robust nonparametric inference on the average treatment effect by BENKESER, D., CARONE, M., VAN DER LAAN, M. J., GILBERT, P. B.

“…Doubly robust estimators are widely used to draw inference about the average effect of a treatment. Such estimators are consistent for the effect of interest…”
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Average direct and indirect causal effects under interference by Hu, Yuchen, Li, Shuangning, Wager, Stefan

“…Summary We propose a definition for the average indirect effect of a binary treatment in the potential outcomes model for causal inference under cross-unit…”
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Scaled sparse linear regression by SUN, TINGNI, ZHANG, CUN-HUI

“…Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse…”
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The horseshoe estimator for sparse signals by Carvalho, Carlos M., Polson, Nicholas G., Scott, James G.

“…This paper proposes a new approach to sparsity, called the horseshoe estimator, which arises from a prior based on multivariate-normal scale mixtures. We…”
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Covariate-assisted spectral clustering by BINKIEWICZ, N., VOGELSTEIN, J. T., ROHE, K.

“…Biological and social systems consist of myriad interacting units. The interactions can be represented in the form of a graph or network. Measurements of these…”
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