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Binary classification is a fundamental task in machine learning, with applications spanning various scientific domains. Whether scientists are conducting fundamental research or refining practical applications, they typically assess and…

Machine Learning · Computer Science 2023-10-20 Attila Fazekas , György Kovács

We analyze safety problems of complex systems using the methods of mathematical statistics for testing the output variables of a code simulating the operation of the system under consideration when the input variables are uncertain. We have…

Data Analysis, Statistics and Probability · Physics 2007-05-23 L. Pal , M. Makai

There are two methods for counting the number of occurrences of a string in another large string. One is to count the number of places where the string is found. The other is to determine how many pieces of string can be extracted without…

Data Structures and Algorithms · Computer Science 2022-11-09 Ayaka Takamoto , Mitsuo Yoshida , Kyoji Umemura

One of the most popular class of tests for independence between two random variables is the general class of rank statistics which are invariant under permutations. This class contains Spearman's coefficient of rank correlation statistic,…

Computation · Statistics 2009-02-04 Ehab F. Abd-Elfattah

In some applications, an experimental unit is composed of two distinct but related subunits. The response from such a unit is $(X_{1}, X_{2})$ but we observe only $Y_1 = \min\{X_{1},X_{2}\}$ and $Y_2 = \max\{X_{1},X_{2}\}$, i.e., the…

Statistics Theory · Mathematics 2019-05-07 Jiahua Chen , Pengfei Li , Jing Qin , Tao Yu

In this paper, the defining properties of a valid measure of the dependence between two random variables are reviewed and complemented with two original ones, shown to be more fundamental than other usual postulates. While other popular…

Methodology · Statistics 2019-12-03 Gery Geenens , Pierre Lafaye de Micheaux

Ordinal categorical data are widely collected in psychology, education, and other social sciences, appearing commonly in questionnaires, assessments, and surveys. Latent class models provide a flexible framework for uncovering unobserved…

Machine Learning · Statistics 2026-02-26 Huan Qing

We analyze the ordinal structure of long-range dependent time series. To this end, we use so called ordinal patterns which describe the relative position of consecutive data points. We provide two estimators for the probabilities of ordinal…

While supporting the execution of business processes, information systems record event logs. Conformance checking relies on these logs to analyze whether the recorded behavior of a process conforms to the behavior of a normative…

Artificial Intelligence · Computer Science 2020-07-07 Han van der Aa , Henrik Leopold , Matthias Weidlich

The problem of testing for the parametric form of the conditional variance is considered in a fully nonparametric regression model. A test statistic based on a weighted $L_2$-distance between the empirical characteristic functions of…

Methodology · Statistics 2018-07-24 Juan Carlos Pardo-Fernandez , M. Dolores Jimenez-Gamero

Comparisons of different treatments or production processes are the goals of a significant fraction of applied research. Unsurprisingly, two-sample problems play a main role in Statistics through natural questions such as `Is the the new…

Methodology · Statistics 2017-09-05 P. C. Álvarez-Esteban , E. del Barrio , J. A. Cuesta-Albertos , C. Matrán

A common method for deriving non-parametric tests is to reformulate a parametric test in terms of sample ranks. Despite being distribution free (even in finite samples), the resulting tests often display remarkable asymptotic power…

Statistics Theory · Mathematics 2022-08-10 Dan D. Erdmann-Pham , Jonathan Terhorst , Yun S. Song

Asymptotic normality of intermediate order statistics taken from univariate iid random variables is well-known. We generalize this result to random vectors in arbitrary dimension, where the order statistics are taken componentwise.

Statistics Theory · Mathematics 2016-07-21 Michael Falk , Florian Wisheckel

This paper focuses on a data-rich environment where the data set has a very large cross-sectional dimension, is likely to exhibit local dependence, and yet is hard to determine the dependence ordering. Such a situation arises, for example,…

Methodology · Statistics 2018-07-03 Kyungchul Song

We present a general framework for hypothesis testing on distributions of sets of individual examples. Sets may represent many common data sources such as groups of observations in time series, collections of words in text or a batch of…

Methodology · Statistics 2021-02-03 Alexis Bellot , Mihaela van der Schaar

We propose two nonparametric statistical tests of goodness of fit for conditional distributions: given a conditional probability density function $p(y|x)$ and a joint sample, decide whether the sample is drawn from $p(y|x)r_x(x)$ for some…

Machine Learning · Statistics 2020-07-01 Wittawat Jitkrittum , Heishiro Kanagawa , Bernhard Schölkopf

A survey of goodness-of-fit and symmetry tests based on the characterization properties of distributions is presented. This approach became popular in recent years. In most cases the test statistics are functionals of $U$-empirical…

Statistics Theory · Mathematics 2017-07-07 Ya. Yu. Nikitin

In this paper we focus on providing sufficient conditions for some well-known stochastic orders in reliability but dealing with the discrete versions of them, filling a gap in the literature. In particular, we find conditions based on the…

Statistics Theory · Mathematics 2026-01-28 F. Belzunce , C. Martínez-Riquelme , M. Pereda

In the first part we associate a periodic sequence to a partition and study the connection the distribution of elements of uniform limit of the sequences. Then some facts of statistical independence of these limits are proved

Number Theory · Mathematics 2018-05-01 Milan Pasteka

We study the problem of conditional two-sample testing, which aims to determine whether two populations have the same distribution after accounting for confounding factors. This problem commonly arises in various applications, such as…

Machine Learning · Statistics 2026-05-05 Seongchan Lee , Suman Cha , Ilmun Kim