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Estimating software testability can crucially assist software managers to optimize test budgets and software quality. In this paper, we propose a new approach that radically differs from the traditional approach of pursuing testability…

Software Engineering · Computer Science 2023-08-01 Luca Guglielmo , Leonardo Mariani , Giovanni Denaro

For many machine learning problems, data is abundant and it may be prohibitive to make multiple passes through the full training set. In this context, we investigate strategies for dynamically increasing the effective sample size, when…

Machine Learning · Computer Science 2016-10-10 Hadi Daneshmand , Aurelien Lucchi , Thomas Hofmann

Determining the sample size of an experiment can be challenging, even more so when incorporating external information via a prior distribution. Such information is increasingly used to reduce the size of the control group in randomized…

Applications · Statistics 2019-07-10 Beat Neuenschwander , Sebastian Weber , Heinz Schmidli , Anthony O'Hagan

Estimation using pooled sampling has long been an area of interest in the group testing literature. Such research has focused primarily on the assumed use of fixed sampling plans (i), although some recent papers have suggested alternative…

Statistics Theory · Mathematics 2017-03-27 Gregory Haber , Yaakov Malinovsky , Paul Albert

The pseudo-marginal algorithm is a popular variant of the Metropolis--Hastings scheme which allows us to sample asymptotically from a target probability density $\pi$, when we are only able to estimate an unnormalized version of $\pi$…

Computation · Statistics 2017-07-20 George Deligiannidis , Arnaud Doucet , Michael K. Pitt

Determination of sample size is critical, however not easy to do. Sample size defined as the number of observations in a sample should be big enough to have a high likelihood of detecting a true difference between groups. Practical…

Methodology · Statistics 2025-02-28 Hoi-Jeong Lim

Background: Under competing risks, the commonly used sub-distribution hazard ratio (SHR) is not easy to interpret clinically and is valid only under the proportional sub-distribution hazard (SDH) assumption. This paper introduces an…

Methodology · Statistics 2020-10-06 Jingjing Lyu , Yawen Hou , Zheng Chen

A computer code can simulate a system's propagation of variation from random inputs to output measures of quality. Our aim here is to estimate a critical output tail probability or quantile without a large Monte Carlo experiment. Instead,…

Machine Learning · Statistics 2019-08-16 Hao Chen , William J. Welch

Researchers in genetics and other life sciences commonly use permutation tests to evaluate differences between groups. Permutation tests have desirable properties, including exactness if data are exchangeable, and are applicable even when…

Computation · Statistics 2018-11-01 Brian Segal , Thomas Braun , Michael Elliott , Hui Jiang

We propose new statistical tests, in high-dimensional settings, for testing the independence of two random vectors and their conditional independence given a third random vector. The key idea is simple, i.e., we first transform each…

Methodology · Statistics 2026-01-28 Jinyuan Chang , Yue Du , Jing He , Qiwei Yao

Bell tests are of profound statistical nature. Besides physical considerations, the proper understanding of their implications should involve detailed statistical analyses. In this regard, recent works have shown that their consequences and…

Quantum Physics · Physics 2025-06-10 Alfredo Luis

Two semimetrics on probability distributions are proposed, given as the sum of differences of expectations of analytic functions evaluated at spatial or frequency locations (i.e, features). The features are chosen so as to maximize the…

Machine Learning · Statistics 2016-10-31 Wittawat Jitkrittum , Zoltan Szabo , Kacper Chwialkowski , Arthur Gretton

Corrected confidence intervals are developed for the mean of the second component of a bivariate normal process when the first component is being monitored sequentially. This is accomplished by constructing a first approximation to a…

Statistics Theory · Mathematics 2007-06-13 R. C. Weng , D. S. Coad

Group sequential designs drive innovation in clinical, industrial, and corporate settings. Early stopping for failure in sequential designs conserves experimental resources, whereas early stopping for success accelerates access to improved…

Methodology · Statistics 2025-11-27 Luke Hagar , Shirin Golchi , Marina B. Klein

A non parametric method based on the empirical likelihood is proposed for detecting the change in the coefficients of high-dimensional linear model where the number of model variables may increase as the sample size increases. This amounts…

Statistics Theory · Mathematics 2015-06-22 Gabriela Ciuperca , Zahraa Salloum

The objective of Bayesian inference is often to infer, from data, a probability measure for a random variable that can be used as input for Monte Carlo simulation. When datasets for Bayesian inference are small, a principle challenge is…

Computation · Statistics 2018-03-29 Jiaxin Zhang , Michael D. Shields

Randomization testing is a fundamental method in statistics, enabling inferential tasks such as testing for (conditional) independence of random variables, constructing confidence intervals in semiparametric location models, and…

Methodology · Statistics 2023-03-21 Yash Nair , Lucas Janson

We analyze theoretical properties of the hybrid test for superior predictability. We demonstrate with a simple example that the test may not be pointwise asymptotically of level $\alpha$ at commonly used significance levels and may lead to…

Econometrics · Economics 2021-09-13 Deborah Kim

In this paper we propose several variants to perform the independence test between two random elements based on recurrence rates. We will show how to calculate the test statistic in each one of these cases. From simulations we obtain that…

Methodology · Statistics 2020-09-21 Juan Kalemkerian , Diego Fernández

Adaptive experiments use preliminary analyses of the data to inform further course of action and are commonly used in many disciplines including medical and social sciences. Because the null hypothesis and experimental design are…

Methodology · Statistics 2026-05-26 Tobias Freidling , Qingyuan Zhao , Zijun Gao