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The methodological contribution in this paper is motivated by biomechanical studies where data characterizing human movement are waveform curves representing joint measures such as flexion angles, velocity, acceleration, and so on. In many…

Methodology · Statistics 2024-02-08 Christian Acal , Ana M. Aguilera

Testing the homogeneity between two samples of functional data is an important task. While this is feasible for intensely measured functional data, we explain why it is challenging for sparsely measured functional data and show what can be…

Methodology · Statistics 2022-07-05 Changbo Zhu , Jane-Ling Wang

In the context of functional data analysis, we propose new two sample tests for homogeneity. Based on some well-known depth measures, we construct four different statistics in order to measure distance between the two samples. A simulation…

Methodology · Statistics 2015-07-08 Ramón Flores , Rosa Lillo , Juan Romo

Suppose that we are interested in the comparison of two independent categorical variables. Suppose also that the population is divided into subpopulations or groups. Notice that the distribution of the target variable may vary across…

Methodology · Statistics 2024-05-08 M. V. Alba-Fernández , M. D. Jiménez--Gamero , F. J. Ariza-López

Data depth has been applied as a nonparametric measurement for ranking multivariate samples. In this paper, we focus on homogeneity tests to assess whether two multivariate samples are from the same distribution. There are many data…

Statistics Theory · Mathematics 2023-06-09 Yiting Chen , Wei Lin , Xiaoping Shi

Resistive Random Access Memories (RRAMs) are being studied by the industry and academia because it is widely accepted that they are promising candidates for the next generation of high density nonvolatile memories. Taking into account the…

While there exists several inferential methods for analyzing functional data in factorial designs, there is a lack of statistical tests that are valid (i) in general designs, (ii) under non-restrictive assumptions on the data generating…

Methodology · Statistics 2023-06-28 Merle Munko , Marc Ditzhaus , Markus Pauly , Łukasz Smaga , Jin-Ting Zhang

We consider inference problems for high-dimensional (HD) functional data with a dense number (T) of repeated measurements taken for a large number of p variables from a small number of n experimental units. The spatial and temporal…

Methodology · Statistics 2020-05-06 Shawn Santo , Ping-Shou Zhong

This paper focuses on the problem of testing the null hypothesis that the regression functions of several populations are equal under a general nonparametric homoscedastic regression model. It is well known that linear kernel regression…

Methodology · Statistics 2023-09-01 Graciela Boente , Juan Carlos Pardo-Fernández

Resonance energy transfer methods are in wide use for evaluating protein-protein interactions and protein conformational changes in living cells. Fluorescence resonance energy transfer (FRET) measures energy transfer as a function of the…

Biomolecules · Quantitative Biology 2011-05-05 Amparo Baíllo , Laura Martínez-Muñoz , Mario Mellado

Economic choices are often stochastic: the same person may make a different choice when facing the same alternatives repeatedly. Standard models assume that the degree of randomness reflects the size of utility differences, but choice…

Theoretical Economics · Economics 2026-05-05 Shuhua Si

The development of data acquisition systems is facilitating the collection of data that are apt to be modelled as functional data. In some applications, the interest lies in the identification of significant differences in group functional…

One of the classic concerns in statistics is determining if two samples come from thesame population, i.e. homogeneity testing. In this paper, we propose a homogeneitytest in the context of Functional Data Analysis, adopting an idea from…

Applications · Statistics 2021-10-22 Alejandro Calle-Saldarriaga , Henry Laniado , Francisco Zuluaga

Detecting and locating changes in highly multivariate data is a major concern in several current statistical applications. In this context, the first contribution of the paper is a novel non-parametric two-sample homogeneity test for…

Statistics Theory · Mathematics 2012-02-13 Alexandre Lung-Yut-Fong , Céline Lévy-Leduc , Olivier Cappé

Functional data analysis is becoming increasingly popular to study data from real-valued random functions. Nevertheless, there is a lack of multiple testing procedures for such data. These are particularly important in factorial designs to…

Methodology · Statistics 2024-06-04 Merle Munko , Marc Ditzhaus , Markus Pauly , Łukasz Smaga

We propose a new approach to the problem of high-dimensional multivariate ANOVA via bootstrapping max statistics that involve the differences of sample mean vectors. The proposed method proceeds via the construction of simultaneous…

Methodology · Statistics 2021-04-20 Zhenhua Lin , Miles E. Lopes , Hans-Georg Müller

This paper considers the problem of testing temporal homogeneity of $p$-dimensional population mean vectors from the repeated measurements of $n$ subjects over $T$ times. To cope with the challenges brought by high-dimensional longitudinal…

Methodology · Statistics 2016-08-29 Ping-Shou Zhong , Jun Li

Ordinal scores occur commonly in medical imaging studies and in black-box forensic studies \citep{Phillips:2018}. To assess the accuracy of raters in the studies, one needs to estimate the receiver operating characteristic (ROC) curve while…

Applications · Statistics 2023-07-19 Ngoc-Ty Nguyen , P. Jonathon Phillips , Larry Tang

Emerging analog resistive random access memory (RRAM) based on HfOx is an attractive device for non-von Neumann neuromorphic computing systems. The differences in temperature dependent conductance drift among cells hamper computing…

Emerging Technologies · Computer Science 2021-11-17 Heng Xu , Yue Sun , Yangyang Zhu , Xiaohu Wang , Guoxuan Qin

We propose a method to impose homogeneous linear inequality constraints of the form $Ax\leq 0$ on neural network activations. The proposed method allows a data-driven training approach to be combined with modeling prior knowledge about the…

Machine Learning · Computer Science 2020-05-29 Thomas Frerix , Matthias Nießner , Daniel Cremers
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