English
Related papers

Related papers: The weighted large sieve through Parseval

200 papers

We give a new bound for the large sieve inequality with power moduli q^k that is uniform in k. The proof uses a new theorem due to T. Wooley from his work on efficient congruencing.

Number Theory · Mathematics 2012-02-28 Karin Halupczok

Several strategies have been developed recently to ensure valid inference after model selection; some of these are easy to compute, while others fare better in terms of inferential power. In this paper, we consider a selective inference…

Methodology · Statistics 2022-07-13 Snigdha Panigrahi , Jonathan Taylor

Several problems in statistics involve the combination of high-variance unbiased estimators with low-variance estimators that are only unbiased under strong assumptions. A notable example is the estimation of causal effects while combining…

Methodology · Statistics 2023-05-25 Michael Oberst , Alexander D'Amour , Minmin Chen , Yuyan Wang , David Sontag , Steve Yadlowsky

The usual chi-squared method of fit quality assessment is a special case of the more general method of Bayesian model comparison which involves integrals of the likelihood and prior over all possible values of all parameters. We introduce…

Nuclear Theory · Physics 2012-06-11 Michiel B. De Kock , Hans C. Eggers , Tamás Csörgő

We study system design problems stated as parameterized stochastic programs with a chance-constraint set. We adopt a Bayesian approach that requires the computation of a posterior predictive integral which is usually intractable. In…

Machine Learning · Statistics 2020-01-07 Prateek Jaiswal , Harsha Honnappa , Vinayak A. Rao

We consider the problem of variable selection in linear models when $p$, the number of potential regressors, may exceed (and perhaps substantially) the sample size $n$ (which is possibly small).

We revisit and generalize the concept of composite likelihood as a method to make a probabilistic inference by aggregation of multiple Bayesian agents, thereby defining a class of predictive models which we call composite Bayesian. This…

Computation · Statistics 2019-04-18 Alexis Roche

The main computational challenge in Bayesian inference is to compute integrals against a high-dimensional posterior distribution. In the past decades, variational inference (VI) has emerged as a tractable approximation to these integrals,…

Statistics Theory · Mathematics 2024-01-09 Anya Katsevich , Philippe Rigollet

In this article, we obtain an explicit version of Heath-Brown's large sieve inequality for quadratic characters and discuss its applications to $L$-functions and quadratic fields.

Number Theory · Mathematics 2026-05-28 Zihao Liu

Over the past few decades, statistical methods for causal inference have made impressive strides, enabling progress across a range of scientific fields. However, much of this methodological development has been confined to individual…

Methodology · Statistics 2025-09-30 Wenqi Shi , José R. Zubizarreta

Gaussian functions are commonly used in different fields, many real signals can be modeled into such form. Research aiming to obtain a precise fitting result for these functions is very meaningful. This manuscript intends to introduce a new…

Methodology · Statistics 2021-03-15 Wei Chen

We introduce an evaluation system designed to compute PARSEVAL measures, offering a viable alternative to \texttt{evalb} commonly used for constituency parsing evaluation. The widely used \texttt{evalb} script has traditionally been…

Computation and Language · Computer Science 2024-05-24 Jungyeul Park , Junrui Wang , Eunkyul Leah Jo , Angela Yoonseo Park

Parameter estimates for associated genetic variants, report ed in the initial discovery samples, are often grossly inflated compared to the values observed in the follow-up replication samples. This type of bias is a consequence of the…

Applications · Statistics 2011-04-15 Lizhen Xu , Radu V. Craiu , Lei Sun

Assuming the bilinear reverse Holder's condition, we character weighted inequalities for the bilinear maximal operator on filtered measure spaces. We also obtain Hytonen-Perez type weighted estimates for the bilinear maximal operator. Our…

Probability · Mathematics 2020-07-21 Wei Chen , Yong Jiao

We consider a method of pairwise variations for smooth optimization problems, which involve polyhedral constraints. It consists in making steps with respect to the difference of two selected extreme points of the feasible set together with…

Optimization and Control · Mathematics 2017-01-12 I. V. Konnov

We discuss a new weighted likelihood method for parametric estimation. The method is motivated by the need for generating a simple estimation strategy which provides a robust solution that is simultaneously fully efficient when the model is…

Methodology · Statistics 2019-08-29 Suman Majumder , Adhidev Biswas , Tania Roy , Subir Kumar Bhandari , Ayanendranath Basu

In this article, we propose new Bayesian methods for selecting and estimating a sparse coefficient vector for skewed heteroscedastic response. Our novel Bayesian procedures effectively estimate the median and other quantile functions,…

Methodology · Statistics 2017-07-04 Libo Wang , Yuanyuan Tang , Debajyoti Sinha , Debdeep Pati , Stuart Lipsitz

The purpose of this short article is to prove some potential estimates that naturally arise in the study of subelliptic Sobolev inequalites for functions. This will allow us to prove a local subelliptic Sobolev inequality with the optimal…

Classical Analysis and ODEs · Mathematics 2015-07-14 Po-Lam Yung

We study the average size of shifted convolution summation terms related to the problem of Quantum Unique Ergodicity on ${\rm SL}_2 (\mathbbm{Z})\backslash \mathbbm{H}$. Establishing an upper-bound sieve method for handling such sums, we…

Number Theory · Mathematics 2008-09-11 Roman Holowinsky

We present estimates of the $p$-concentration ratio for various function spaces on different geometries including the line, the sphere, the plane, and the hyperbolic disc, using large sieve methods. Thereby, we focus on $L^{1}$-estimates…

Functional Analysis · Mathematics 2019-02-04 Luís Daniel Abreu , Michael Speckbacher