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Having a regression model, we are interested in finding two-sided intervals that are guaranteed to contain at least a desired proportion of the conditional distribution of the response variable given a specific combination of predictors. We…

Machine Learning · Computer Science 2016-03-22 Mohammad Ghasemi Hamed , Mathieu Serrurier , Nicolas Durand

We consider estimation and inference in a linear model with endogenous regressors where the parameters of interest change across two samples. If the first-stage is common, we show how to use this information to obtain more efficient…

Econometrics · Economics 2024-06-26 Bertille Antoine , Otilia Boldea , Niccolo Zaccaria

In this paper, we have established a new framework of truncated inverse sampling for estimating mean values of non-negative random variables such as binomial, Poisson, hyper-geometrical, and bounded variables. We have derived explicit…

Statistics Theory · Mathematics 2013-11-05 Xinjia Chen

We obtain a lower bound for \[ \#\{x/2< p_{n}\leq x:\ p_n \equiv\ldots\equiv p_{n+m}\equiv a\text{ (mod $q$)},\ p_{n+m} - p_{n}\leq y\}, \] where $p_{n}$ is the $n^{\text{th}}$ prime.

Number Theory · Mathematics 2021-10-19 Artyom Radomskii

Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems. Most improvements of the basic Gauss-Newton algorithm tackle convergence guarantees or leverage the sparsity of the underlying…

Computer Vision and Pattern Recognition · Computer Science 2020-10-22 Huu Le , Christopher Zach , Edward Rosten , Oliver J. Woodford

We prove versions of Goldbach conjectures for Gaussian primes in arbitrary sectors. Fix an interval $\omega \subset \mathbb{T}$. There is an integer $N_\omega $, so that every odd integer $n$ with $N(n)>N_\omega $ and $\text{dist}(…

Number Theory · Mathematics 2024-03-21 Christina Giannitsi , Ben Krause , Michael Lacey , Hamed Mousavi , Yaghoub Rahimi

Linear Least Squares is a very well known technique for parameter estimation, which is used even when sub-optimal, because of its very low computational requirements and the fact that exact knowledge of the noise statistics is not required.…

Statistics Theory · Mathematics 2018-10-16 Michael Krikheli , Amir Leshem

The inferential models (IM) framework provides prior-free, frequency-calibrated, posterior probabilistic inference. The key is the use of random sets to predict unobservable auxiliary variables connected to the observable data and unknown…

Statistics Theory · Mathematics 2016-01-26 Ryan Martin , Chuanhai Liu

Importance sampling is a widely used technique to reduce the variance of a Monte Carlo estimator by an appropriate change of measure. In this work, we study importance sam- pling in the framework of diffusion process and consider the change…

Probability · Mathematics 2018-03-28 Carsten Hartmann , Christof Schütte , Marcus Weber , Wei Zhang

The number of non-negative integer matrices with given row and column sums appears in a variety of problems in mathematics and statistics but no closed-form expression for it is known, so we rely on approximations of various kinds. Here we…

Computation · Statistics 2024-01-25 Maximilian Jerdee , Alec Kirkley , M. E. J. Newman

Quasi-Monte Carlo (qMC) methods are a powerful alternative to classical Monte-Carlo (MC) integration. Under certain conditions, they can approximate the desired integral at a faster rate than the usual Central Limit Theorem, resulting in…

Econometrics · Economics 2019-11-22 Jean-Jacques Forneron

We present a lightweight approach to sequence classification using Ensemble Methods for Hidden Markov Models (HMMs). HMMs offer significant advantages in scenarios with imbalanced or smaller datasets due to their simplicity,…

Machine Learning · Computer Science 2024-09-13 Maxime Kawawa-Beaudan , Srijan Sood , Soham Palande , Ganapathy Mani , Tucker Balch , Manuela Veloso

For any class of one-sided $1-\alpha$ confidence intervals with a certain monotonicity ordering on the random confidence limit, the smallest interval, in the sense of the set inclusion for the difference of two proportions of two…

Statistics Theory · Mathematics 2012-11-19 Weizhen Wang

In the present work we investigate the largest possible gaps between consecutive numbers which can be written as the difference of two primes. The best known upper bounds are the same as those concerning the largest possible difference of…

Number Theory · Mathematics 2012-06-04 Janos Pintz

We give a large sieve type inequality for functions supported on primes. As application we prove a conjecture by Elliott, and give bounds for short character sums over primes. The proves uses a combination of the large sieve and the Selberg…

Number Theory · Mathematics 2011-05-10 Jan-Christoph Schlage-Puchta

It is a common contention that it is an ``impossible mission'' to exactly determine the minimum sample size for the estimation of a binomial parameter with prescribed margin of error and confidence level. In this paper, we investigate such…

Statistics Theory · Mathematics 2007-08-02 Xinjia Chen

This paper deals with subsampled spectral gradient methods for minimizing finite sum. Subsample function and gradient approximations are employed in order to reduce the overall computational cost of the classical spectral gradient methods.…

Numerical Analysis · Mathematics 2019-11-04 Stefania Bellavia , Nataša Krklec Jerinkić , Greta Malaspina

Gross and Smith have put forward generalizations of Hardy - Littlewood twin prime conjectures for algebraic number fields. We estimate the behavior of sums of a singular series that arises in these conjectures, up to lower order terms. More…

Number Theory · Mathematics 2020-01-28 Vivian Kuperberg , Brad Rodgers , Edva Roditty-Gershon

Let $X$ be large and let $\mathcal{P}$ denote the set of primes. Fix positive real parameters $r_1,\dots,r_s$ and a parameter $\lambda\geqslant 1$ determined by a balancing relation, and let $\mathcal{A}_{\lambda}(X)\subset[1,2X]$ be the…

Number Theory · Mathematics 2026-04-24 Yuchen Ding , Johann Verwee

We study a class of statistical inverse problems with non-linear pointwise operators motivated by concrete statistical applications. A two-step procedure is proposed, where the first step smoothes the data and inverts the non-linearity.…

Statistics Theory · Mathematics 2016-11-08 Kolyan Ray , Johannes Schmidt-Hieber