A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
The article compares predictor importance in classification problems with categorical outcomes.
Identifying statistical dependence between the features and the label is a fundamental problem in supervised learning. This paper presents a framework for estimating dependence between numerical features and a categorical label using generalized Gini distance, an energy distance in reproducing kernel Hilbert spaces (RK…
A new method for Gaussian Processes handles mixed continuous and categorical inputs.
Gini index needs auto-calibration for consistent decision-making.
New Gini indices capture more nuanced income inequality.
Adaptive correlated MC improves sequence generation stability.
Paper discusses extending Gini score for tied rankings and case weights.
Novel method for multiclass ROC curves using multidimensional Gini index.
The paper examines the stability of binary choice models using Gini index and scoring indicators.
Proposes a simple solution to Gini importance bias in random forests.
We propose an approach to explain fluctuations in time intervals of financial markets data from the view point of the Gini index. We show the explicit form of the Gini index for a Weibull distribution which is a good candidate to describe the first passage time of foreign exchange rate. The analytical expression of the…
A new method selects representative subdata without assuming underlying models.
Paper proves convergence of Gini index to equilibrium in Wasserstein distance.
The evolution of Gini coefficient for personal incomes in the USA between 1947 and 2005 is analyzed and modeled. There are several versions of personal income distribution (PID) provided by the US Census Bureau (US CB) for this period with various levels of resolution. Effectively, these PIDs result in different Gini c…
New GP kernel handles mixed-categorical data, improving model accuracy.
Analytical results bound the approach to oligarchy in a modified asset exchange model.
In this paper, we establish the stochastic ordering of the Gini indexes for multivariate elliptical risks which generalized the corresponding results for multivariate normal risks. It is shown that several conditions on dispersion matrices and the components of dispersion matrices of multivariate normal risks for the m…
Rapidly growing product lines and services require a finer-granularity forecast that considers geographic locales. However the open question remains, how to assess the quality of a spatio-temporal forecast? In this manuscript we introduce a metric to evaluate spatio-temporal forecasts. This metric is based on an Opti- …
The paper analyzes worst-case distortion risk metrics and weighted entropy under partial information.
The aim of this paper is to introduce a risk measure that extends the Gini-type measures of risk and variability, the Extended Gini Shortfall, by taking risk aversion into consideration. Our risk measure is coherent and catches variability, an important concept for risk management. The analysis is made under the Choque…
Paper introduces a new measure combining entropy and Gini index.
Direct measurements of Gini coefficients by conventional arithmetic calculations are a poor estimator, even if paradoxically, they include the entire population, as because of super-additivity they cannot lend themselves to comparisons between units of different size, and intertemporal analyses are vitiated by the popu…
In many scientific tasks we are interested in discovering whether there exist any correlations in our data. This raises many questions, such as how to reliably and interpretably measure correlation between a multivariate set of attributes, how to do so without having to make assumptions on distribution of the data or t…
We study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index ). We show that, in such a case, the Gini coefficient cannot be reliably estimated usin…
We study the problem of recovering the latent ground truth labeling of a structured instance with categorical random variables in the presence of noisy observations. We present a new approximate algorithm for graphs with categorical variables that achieves low Hamming error in the presence of noisy vertex and edge obse…
Two regularization techniques improve GCNN explainability and preference from chemists.
DPERC efficiently estimates covariance matrices for mixed data with missing values.
Statistical evaluations of the economic mobility of a society are more difficult than measurements of the income distribution, because they require to follow the evolution of the individuals' income for at least one or two generations. In micro-to-macro theoretical models of economic exchanges based on kinetic equation…
A new method tests independence for causal discovery on discrete data.
The standard deviation and Gini mean difference order based on tail behavior.
Punctuated Equilibrium (PE) states that after long periods of evolutionary quiescence, species evolution can take place in short time intervals, where sudden differentiation makes new species emerge and some species extinct. In this paper, we introduce and study the effect of punctuated equilibrium on two different ass…
CARMS improves gradient estimation for categorical variables.
This paper fills in local bounds for Spearman's footrule and Gini's gamma measures of association.
A society or country with income equally distributed among its people is truly a fiction! The phenomena of socioeconomic inequalities have been plaguing mankind from times immemorial. We are interested in gaining an insight about the co-evolution of the countries in the inequality space, from a data science perspective…
The argument that the alarming level of Gini coefficient is 0.4 is very popular, especially in the media industry, all around the world for a long time. Although the 0.4 standard is widely accepted, the derivation of the value lacks rigid theoretical foundations. In fact, to the best of our knowledge, it is not based o…
The paper covers the new model of wage distribution in typical group of people. The model provides the opportunity to reparameterize applicable income distribution model: Pareto, logarithmically normal, logarithmically logistic, Dagum etc. The model ensures the graduation of Gini index values by polynomial degree of wa…
WE constructs GP kernels for mixed inputs using weighted EDMs.
Wealth redistribution through Fokker-Planck equation controls preserves Gini coefficient.
Baseline injury categorization is important to traumatic brain injury (TBI) research and treatment. Current categorization is dominated by symptom-based scores that insufficiently capture injury heterogeneity. In this work, we apply unsupervised clustering to identify novel TBI phenotypes. Our approach uses a generaliz…
Socio-economic inequality is characterized from data using various indices. The Gini () index, giving the overall inequality is the most common one, while the recently introduced Kolkata () index gives a measure of fraction of population who possess top fraction of wealth in the society. Here, we show t…
The CAP slope is Bayes' theorem in cumulative coordinates, unlocking the weight of evidence, Somers' D, and Gini coefficient.
The paper calculates bounds for risk metrics and entropies under partial information constraints.
Systematizes blockchain decentralization taxonomy and metrics.
Using tax and census data, we demonstrate that the distribution of individual income in the USA is exponential. Our calculated Lorenz curve without fitting parameters and Gini coefficient 1/2 agree well with the data. From the individual income distribution, we derive the distribution function of income for families wi…
Many models of market dynamics make use of the idea of conservative wealth exchanges among economic agents. A few years ago an exchange model using extremal dynamics was developed and a very interesting result was obtained: a self-generated minimum wealth or poverty line. On the other hand, the wealth distribution exhi…
Framework monitors insurance pricing models for drift and recalibration.
Gryffin optimizes categorical variables in materials design, leveraging expert knowledge.
Linear stochastic models and discretized kinetic theory are two complementary analytical techniques used for the investigation of complex systems of economic interactions. The former employ Langevin equations, with an emphasis on stock trade; the latter is based on systems of ordinary differential equations and is bett…