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Related papers: The Regression Discontinuity Design

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We propose a novel approach for loss reserving based on deep neural networks. The approach allows for joint modeling of paid losses and claims outstanding, and incorporation of heterogeneous inputs. We validate the models on loss reserving…

Applications · Statistics 2019-09-17 Kevin Kuo

Errors in variables (Deming) regression of measurements spanning a wide range of values requires appropriate weighting to reflect nonconstant variance. Precision profile models, mathematical relationships between measurement variance and…

Computation · Statistics 2025-08-06 Douglas M Hawkins , Jessica J Kraker

Traditional regression and prediction tasks often only provide deterministic point estimates. To estimate the distribution or uncertainty of the response variable, traditional methods either assume that the posterior distribution of samples…

Machine Learning · Computer Science 2025-01-08 Daojun Liang , Haixia Zhang , Dongfeng Yuan

The Regression Discontinuity Design (RDD) is a quasi-experimental design that estimates the causal effect of a treatment when its assignment is defined by a threshold value for a continuous assignment variable. The RDD assumes that subjects…

Applications · Statistics 2020-03-27 Federico Ricciardi , Silvia Liverani , Gianluca Baio

For non-randomized studies, the regression discontinuity design (RDD) can be used to identify and estimate causal effects from a "locally-randomized" subgroup of subjects, under relatively mild conditions. However, current models focus…

Methodology · Statistics 2015-02-12 George Karabatsos , Stephen G. Walker

Stuttering is a speech disorder during which the flow of speech is interrupted by involuntary pauses and repetition of sounds. Stuttering identification is an interesting interdisciplinary domain research problem which involves pathology,…

Sound · Computer Science 2022-11-17 Shakeel Ahmad Sheikh , Md Sahidullah , Fabrice Hirsch , Slim Ouni

In this paper, a general methodology to study rigorously discontinuities in open waveguides is presented. It relies on a full vector description given by Maxwell's equations in the framework of the finite element method. The discontinuities…

Computational Physics · Physics 2020-06-24 Guillaume Demésy , Gilles Renversez

Predicting the number of defects in a project is critical for project test managers to allocate budget, resources, and schedule for testing, support and maintenance efforts. Software Defect Prediction models predict the number of defects in…

Software Engineering · Computer Science 2023-06-16 Susmita Haldar , Luiz Fernando Capretz

This paper focuses on the application of soft computing in remanufacturing system, in which end-of-life products are disassembled into basic components and then remanufactured for both economic and environmental reasons. The disassembly…

Other Computer Science · Computer Science 2012-06-06 Bo Xing , Wen-Jing Gao , Fulufhelo V. Nelwamondo , Kimberly Battle , Tshilidzi Marwala

We introduce new variants of classical regression-based algorithms for optimal stopping problems based on computation of regression coefficients by Monte Carlo approximation of the corresponding $L^2$ inner products instead of the…

Computational Finance · Quantitative Finance 2019-04-29 Christian Bayer , Martin Redmann , John Schoenmakers

The causal inference model proposed by Lee (2008) for the regression discontinuity design (RDD) relies on assumptions that imply the continuity of the density of the assignment (running) variable. The test for this implication is commonly…

Econometrics · Economics 2024-06-28 Federico Crippa

In this work, we discuss what we refer to as reduction techniques for survival analysis, that is, techniques that "reduce" a survival task to a more common regression or classification task, without ignoring the specifics of survival data.…

This is a short tutorial about different software design methodologies.

Software Engineering · Computer Science 2014-03-18 Reza Rahimi

Causal inference, as a major research area in statistics and data science, plays a central role across diverse fields such as medicine, economics, education, and the social sciences. Design-based causal inference begins with randomized…

Methodology · Statistics 2025-12-01 Xin Lu , Wanjia Fu , Hongzi Li , Haoyang Yu , Honghao Zhang , Ke Zhu , Hanzhong Liu

Educational guide focused on the statistical treatment of measurement uncertainties. The conditions of application of current practices are detailed and precised: mean values, central limit theorem, linear regression. The last two chapters…

Other Statistics · Statistics 2020-07-15 Romain Legrand

Regression discontinuity (RD) is a widely used quasi-experimental design for causal inference. In the standard RD, the assignment to treatment is determined by a continuous pretreatment variable (i.e., running variable) falling above or…

Methodology · Statistics 2020-06-23 Fan Li , Andrea Mercatanti , Taneli Makinen , Andrea Silvestrini

This document is written in order to establish a common base ground on which the majority of the relevant research about linear fountain codes can be analyzed and compared. As far as I am concerned, there is no unified approach that…

Information Theory · Computer Science 2014-07-16 Suayb S. Arslan

Ordinal regression refers to classifying object instances into ordinal categories. Ordinal regression is crucial for applications in various areas like facial age estimation, image aesthetics assessment, and even cancer staging, due to its…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Jinhong Wang , Jintai Chen , Jian Liu , Dongqi Tang , Danny Z. Chen , Jian Wu

Under the International Financial Reporting Standards (IFRS) 9, credit losses ought to be recognised timeously and accurately. This requirement belies a certain degree of dynamicity when estimating the constituent parts of a credit loss…

Risk Management · Quantitative Finance 2025-12-16 Arno Botha , Tanja Verster

This paper introduces an effcient class of adaptive stencil extension reconstruction methods based on a discontinuity feedback factor, addressing the challenges of weak robustness and high computational cost in high-order schemes,…

Numerical Analysis · Mathematics 2024-10-10 Hong Zhang , Yue Zhao , Xing Ji , Kun Xu