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Fisher's exact test is often a preferred method to estimate the significance of statistical dependence. However, in large data sets the test is usually too worksome to be applied, especially in an exhaustive search (data mining). The…

Computation · Statistics 2014-05-07 Wilhelmiina Hämäläinen

Information coefficient (IC) is a widely used metric for measuring investment managers' skills in selecting stocks. However, its adequacy and effectiveness for evaluating stock selection models has not been clearly understood, as IC from a…

Computational Finance · Quantitative Finance 2020-10-20 Feng Zhang , Ruite Guo , Honggao Cao

This paper provides a systematic approach to semiparametric identification that is based on statistical information as a measure of its "quality". Identification can be regular or irregular, depending on whether the Fisher information for…

Statistics Theory · Mathematics 2021-07-01 Juan Carlos Escanciano

In a globalised world, inflation in a given country may be becoming less responsive to domestic economic activity, while being increasingly determined by international conditions. Consequently, understanding the international sources of…

Econometrics · Economics 2024-10-30 Ignacio Garrón , C. Vladimir Rodríguez-Caballero , Esther Ruiz

Two network measures known as the Economic Complexity Index (ECI) and Product Complexity Index (PCI) have provided important insights into patterns of economic development. We show that the ECI and PCI are equivalent to a spectral…

Economics · Quantitative Finance 2021-10-05 Penny Mealy , J. Doyne Farmer , Alexander Teytelboym

Although empirical literature regarding the Phillips curve is sizeable enough, there is still no wide consensus on its validity and stability. The literature shows that the Phillips relationship is fragile and varies across countries and…

General Economics · Economics 2025-12-01 Yhlas Sovbetov , Muhittin Kaplan

In an attempt to provide an answer to the increasing criticism against p-values and to bridge the gap between statistical inference and prediction modelling, we introduce the probability of improved prediction (PIP). In general, the PIP is…

Methodology · Statistics 2024-05-28 Olivier Thas , Stijn Jaspers

Statistical methods for automatically identifying dependent word pairs (i.e. dependent bigrams) in a corpus of natural language text have traditionally been performed using asymptotic tests of significance. This paper suggests that Fisher's…

cmp-lg · Computer Science 2008-02-03 Ted Pedersen

The development of statistical methods for valid and efficient probabilistic inference without prior distributions has a long history. Fisher's fiducial inference is perhaps the most famous of these attempts. We argue that, despite its…

Statistics Theory · Mathematics 2015-01-20 Chuanhai Liu , Ryan Martin

A standard goal of model evaluation and selection is to find a model that approximates the truth well while at the same time is as parsimonious as possible. In this paper we emphasize the point of view that the models under consideration…

Methodology · Statistics 2010-10-05 Bruce Lindsay , Jiawei Liu

This short study presents an opportunistic approach to a (more) reliable validation method for prediction uncertainty average calibration. Considering that variance-based calibration metrics (ZMS, NLL, RCE...) are quite sensitive to the…

Machine Learning · Statistics 2024-08-27 Pascal Pernot

We propose measurement integrity, a property related to ex post reward fairness, as a novel desideratum for peer prediction mechanisms in many natural applications. Like robustness against strategic reporting, the property that has been the…

Computer Science and Game Theory · Computer Science 2022-09-26 Noah Burrell , Grant Schoenebeck

In this era of Big Data, proficient use of data mining is the key to capture useful information from any dataset. As numerous data mining techniques make use of information theory concepts, in this paper, we discuss how Fisher information…

Information Theory · Computer Science 2016-11-17 Nasir Ahmad , Sybil Derrible , Tarsha Eason , Heriberto Cabezas

Reachability analysis is a critical tool for the formal verification of dynamical systems and the synthesis of controllers for them. Due to their computational complexity, many reachability analysis methods are restricted to systems with…

Systems and Control · Electrical Eng. & Systems 2020-07-14 Alex Devonport , Mahmoud Khaled , Murat Arcak , Majid Zamani

A public decision-making problem consists of a set of issues, each with multiple possible alternatives, and a set of competing agents, each with a preferred alternative for each issue. We study adaptations of market economies to this…

Computer Science and Game Theory · Computer Science 2019-07-23 Nikhil Garg , Ashish Goel , Benjamin Plaut

The maximal information coefficient (MIC) is a tool for finding the strongest pairwise relationships in a data set with many variables (Reshef et al., 2011). MIC is useful because it gives similar scores to equally noisy relationships of…

Methodology · Statistics 2015-05-13 Yakir A. Reshef , David N. Reshef , Pardis C. Sabeti , Michael Mitzenmacher

In model selection literature, two classes of criteria perform well asymptotically in different situations: Bayesian information criterion (BIC) (as a representative) is consistent in selection when the true model is finite dimensional…

Statistics Theory · Mathematics 2012-02-03 Wei Liu , Yuhong Yang

The use of bibliometric indicators would simplify research assessments. The 2014 Research Excellence Framework (REF) is a peer review assessment of UK universities, whose results can be taken as benchmarks for bibliometric indicators. In…

Digital Libraries · Computer Science 2020-02-18 Alonso Rodriguez Navarro , Ricardo Brito

Over the past five decades a number of multilateral index number systems have been proposed for spatial and cross-country price comparisons. These multilateral indexes are usually expressed as solutions to systems of linear or nonlinear…

Theoretical Economics · Economics 2018-12-17 Gholamreza Hajargasht , Prasada Rao

A common approach to analyzing categorical correlated time series data is to fit a generalized linear model (GLM) with past data as covariate inputs. There remain challenges to conducting inference for short time series length. By treating…

Statistics Theory · Mathematics 2018-10-23 Xu Gao , Hernando Ombao , Daniel Gillen