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This paper presents a new approach to conditional inference, based on the simulation of samples conditioned by a statistics of the data. Also an explicit expression for the approximation of the conditional likelihood of long runs of the…

Applications · Statistics 2012-02-07 Michel Broniatowski , Virgile Caron

Due to the limitations of the robotic sensors, during a robotic manipulation task, the acquisition of the object's state can be unreliable and noisy. Combining an accurate model of multi-body dynamic system with Bayesian filtering methods…

Robotics · Computer Science 2023-10-10 Shuai Li , Siwei Lyu , Jeff Trinkle

Statistical applications in sports have long centered on how to best separate signal (e.g. team talent) from random noise. However, most of this work has concentrated on a single sport, and the development of meaningful cross-sport…

Applications · Statistics 2017-11-23 Michael J. Lopez , Gregory J. Matthews , Benjamin S. Baumer

The speed-accuracy tradeoffs are prevalent in a wide range of physical systems. In this paper, we demonstrate speed-accuracy tradeoffs in the game of cricket, where 'batters' score runs on the balls bowled by the 'bowlers'. It is shown that…

Physics and Society · Physics 2025-12-17 Mohd Suhail Rizvi

The Rao-Blackwell theorem is utilized to analyze and improve the scalability of inference in large probabilistic models that exhibit symmetries. A novel marginal density estimator is introduced and shown both analytically and empirically to…

Artificial Intelligence · Computer Science 2013-04-10 Mathias Niepert

An enduring issue in higher education is student retention to successful graduation. National statistics indicate that most higher education institutions have four-year degree completion rates around 50 percent, or just half of their…

Computers and Society · Computer Science 2020-10-08 Mack Sweeney , Huzefa Rangwala , Jaime Lester , Aditya Johri

We introduce a new online algorithm for expected log-likelihood maximization in situations where the objective function is multi-modal and/or has saddle points, that we term G-PFSO. The key element underpinning G-PFSO is a probability…

Machine Learning · Statistics 2022-07-07 Mathieu Gerber , Randal Douc

Previous work on fantasy basketball quantifies player value for category leagues without taking draft circumstances into account. Quantifying value in this way is convenient, but inherently limited as a strategy, because it precludes the…

Methodology · Statistics 2024-09-17 Zach Rosenof

The hot-hand theory posits that an athlete who has performed well in the recent past performs better in the present. We use multilevel logistic regression to test this theory for National Hockey League playoff goaltenders, controlling for a…

Applications · Statistics 2024-05-13 Likang Ding , Ivor Cribben , Armann Ingolfsson , Monica Tran

In this paper, we present a new model for ranking sports teams. Our model uses all scoring data from all games to produce a functional rating by the method of least squares. The functional rating can be interpreted as a teams average point…

Applications · Statistics 2019-08-05 Bradley Lowery , Abigail Slater , Kaison Thies

We wish to compute the gradient of an expectation over a finite or countably infinite sample space having $K \leq \infty$ categories. When $K$ is indeed infinite, or finite but very large, the relevant summation is intractable. Accordingly,…

Machine Learning · Statistics 2019-05-14 Runjing Liu , Jeffrey Regier , Nilesh Tripuraneni , Michael I. Jordan , Jon McAuliffe

The field of quantitative analytics has transformed the world of sports over the last decade. To date, these analytic approaches are statistical at their core, characterizing what is and what was, while using this information to drive…

Computer Science and Game Theory · Computer Science 2021-10-12 Connor Douglas , Everett Witt , Mia Bendy , Yevgeniy Vorobeychik

During the last few sports seasons a lot of discussion has been generated for the several, high-profile, "comebacks" that were observed in almost all sports. The Cavaliers won the championship after being down 3-1 in the 2016 NBA finals'…

Applications · Statistics 2018-03-15 Konstantinos Pelechrinis

Huge amounts of money are invested every year by football clubs on transfers. For both growth and survival, it is crucial for recruiting departments to make smart choices when targeting players. Therefore, it is very important to identify…

A typical approach to quantify the contribution of each player in basketball uses the plus-minus method. The ratings obtained by such a method are estimated using simple regression models and their regularized variants, with response…

Applications · Statistics 2024-11-01 Argyro Damoulaki , Ioannis Ntzoufras , Konstantinos Pelechrinis

This paper generalizes the notion of sufficiency for estimation problems beyond maximum likelihood. In particular, we consider estimation problems based on Jones et al. and Basu et al. likelihood functions that are popular among…

Statistics Theory · Mathematics 2024-02-29 Atin Gayen , M. Ashok Kumar

We consider the problem of parameter estimation for a class of continuous-time state space models. In particular, we explore the case of a partially observed diffusion, with data also arriving according to a diffusion process. Based upon a…

Computation · Statistics 2021-03-16 Alexandros Beskos , Dan Crisan , Ajay Jasra , Nikolas Kantas , Hamza Ruzayqat

We extract and use player position time-series data, tagged along with the action types, to build a competent model for representing team tactics behavioral patterns and use this representation to predict the outcome of arbitrary movements.…

Machine Learning · Computer Science 2021-09-17 Omid Shokrollahi , Bahman Rohani , Amin Nobakhti

Poyiadjis et al. (2011) show how particle methods can be used to estimate both the score and the observed information matrix for state space models. These methods either suffer from a computational cost that is quadratic in the number of…

Computation · Statistics 2015-09-07 Christopher Nemeth , Paul Fearnhead , Lyudmila Mihaylova

Each ballpark has a different size in baseball. It could be easily imagined that there would be many home runs in a small ballpark. Moreover, the environment of the ballpark, such as altitude, humidity, air pressure, and wind strength,…

Applications · Statistics 2021-09-21 Eiji Konaka