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Synthetic indices are used in Economics to measure various aspects of monetary inequalities. These scalar indices take as input the distribution over a finite population, for example the population of a specific country. In this article we…

Applications · Statistics 2011-09-06 Eric Gautier

In the nano era in integrated circuit fabrication technologies, the performance variability due to statistical process and circuit parameter variations is becoming more and more significant. Considerable effort has been expended in the EDA…

Other Computer Science · Computer Science 2009-09-29 Alp Arslan Bayrakci , Alper Demir , Serdar Tasiran

We derive the asymptotic theory of Bai (2009)'s interactive fixed effects estimator for unbalanced panels in which the source of attrition is conditionally random. For inference, we propose a method of alternating projections algorithm…

Econometrics · Economics 2026-05-19 Daniel Czarnowske , Amrei Stammann

In this paper we develop a methodology that we call split sampling methods to estimate high dimensional expectations and rare event probabilities. Split sampling uses an auxiliary variable MCMC simulation and expresses the expectation of…

Computation · Statistics 2013-11-04 John R. Birge , Changgee Chang , Nicholas G. Polson

A combination of implicit and explicit timestepping is analyzed for a system of ODEs motivated by ones arising from spatial discretizations of evolutionary partial differential equations. Loosely speaking, the method we consider is implicit…

Numerical Analysis · Mathematics 2025-10-20 Mihai Anitescu , William J. Layton , Faranak Pahlevani

The authors examine the concept of probability of default for asset-backed loans. In contrast to unsecured loans it is shown that probability of default can be defined as either a measure of the likelihood of the borrower failing to make…

Risk Management · Quantitative Finance 2013-07-01 David Chisholm , Graham Andersen

The writers propose a mathematical Method for deriving risk weights which describe how a borrower's income, relative to their debt service obligations (serviceability) affects the probability of default of the loan. The Method considers the…

Risk Management · Quantitative Finance 2011-11-24 Graham Andersen , David Chisholm

Density regression provides a flexible strategy for modeling the distribution of a response variable $Y$ given predictors $\mathbf{X}=(X_1,\ldots,X_p)$ by letting that the conditional density of $Y$ given $\mathbf{X}$ as a completely…

Statistics Theory · Mathematics 2016-01-07 Weining Shen , Subhashis Ghosal

The Interbank Offered Rate is a vital benchmark interest rate in the financial markets of every country to which financial contracts are tied. In the light of the recent LIBOR manipulation incident, this paper seeks to address the fear that…

Statistical Finance · Quantitative Finance 2012-08-15 Murphy Choy , Enoch Chng , Koo Ping Shung

Linear programming (LP) is an extremely useful tool and has been successfully applied to solve various problems in a wide range of areas, including operations research, engineering, economics, or even more abstract mathematical areas such…

Data Structures and Algorithms · Computer Science 2020-03-19 Agniva Chowdhury , Palma London , Haim Avron , Petros Drineas

A computational tool for coarse-graining nonlinear systems of ordinary differential equations in time is discussed. Three illustrative model examples are worked out that demonstrate the range of capability of the method. This includes the…

Numerical Analysis · Mathematics 2017-11-23 Sabyasachi Chatterjee , Amit Acharya , Zvi Artstein

A popular version of the finite strain Maxwell fluid is considered, which is based on the multiplicative decomposition of the deformation gradient tensor. The model combines Newtonian viscosity with hyperelasticity of Mooney-Rivlin type; it…

Numerical Analysis · Mathematics 2021-03-15 A. V. Shutov

We apply the technique of implicit differentiation to boost performance, reduce numerical error, and remove required user-tuning in the Marginal Unbiased Score Expansion (MUSE) algorithm for hierarchical Bayesian inference. We demonstrate…

Machine Learning · Statistics 2022-09-22 Marius Millea

The practice of speculative decoding, whereby inference is probabilistically supported by a smaller, cheaper, ``drafter'' model, has become a standard technique for systematically reducing the decoding time of large language models. This…

Computation and Language · Computer Science 2025-10-03 Jameson Sandler , Ahmet Üstün , Marco Romanelli , Sara Hooker , Ferdinando Fioretto

This paper aims to reevaluate the Taylor Rule, through a linear and a nonlinear method, such that its estimated federal funds rates match those actually previously implemented by the Federal Reserve Bank. In the linear method, this paper…

General Economics · Economics 2023-02-17 Alper Deniz Karakas

An efficient method to price bonds with optional sinking feature is presented. Such instruments equip their issuer with the option (but not the obligation) to redeem parts of the notional prior to maturity, therefore the future cash flows…

Pricing of Securities · Quantitative Finance 2013-05-23 Jan-Frederik Mai , Marc Wittlinger

To improve nonparametric estimates of lifetime distributions, we propose using the increasing odds rate (IOR) model as an alternative to other popular, but more restrictive, ``adverse ageing'' models, such as the increasing hazard rate one.…

Methodology · Statistics 2022-12-13 Tommaso Lando , Idir Arab , Paulo Eduardo Oliveira

Recent literature seek to forecast implied volatility derived from equity, index, foreign exchange, and interest rate options using latent factor and parametric frameworks. Motivated by increased public attention borne out of the…

Statistical Finance · Quantitative Finance 2020-09-22 Fearghal Kearney , Han Lin Shang , Lisa Sheenan

Machine learning systems are increasingly being used to make impactful decisions such as loan applications and criminal justice risk assessments, and as such, ensuring fairness of these systems is critical. This is often challenging as the…

Machine Learning · Computer Science 2020-12-18 YooJung Choi , Meihua Dang , Guy Van den Broeck

Distributed averaging, or distributed average consensus, is a common method for computing the sample mean of the data dispersed among the nodes of a network in a decentralized manner. By iteratively exchanging messages with neighbors, the…

Information Theory · Computer Science 2017-10-26 Ryan Pilgrim , Junan Zhu , Dror Baron , Waheed U. Bajwa