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Non‐parametric regression for networks [PDF]
Stat, 2021 Network data are becoming increasingly available, and so there is a need to develop a suitable methodology for statistical analysis. Networks can be represented as graph Laplacian matrices, which are a type of manifold‐valued data. Our main objective is to estimate a regression curve from a sample of graph Laplacian matrices conditional on a set of ...
Katie E. Severn +2 more
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Non Parametric ROC Summary Statistics
Revstat Statistical Journal, 2022 Receiver operating characteristic (ROC) curves are useful statistical tools for medical diagnostic testing. It has been proved its capability to assess diagnostic marker’s ability to distinguish between healthy and diseased subjects and to compare ...
M.C. Pardo , A.M. Franco-Pereira
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Non-parametric parametricity [PDF]
Journal of Functional Programming, 2009 AbstractType abstraction and intensional type analysis are features seemingly at odds—type abstraction is intended to guarantee parametricity and representation independence, while type analysis is inherently non-parametric. Recently, however, several researchers have proposed and implemented “dynamic type generation” as a way to reconcile these ...
Neis, G., Dreyer, D., Rossberg, A.
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Assessment of Trend in Groundwater Level using Hybrid Mann-Kendall and Wavelet Transform Method (Case Study: Ardabil Plain) [PDF]
محیط زیست و مهندسی آب, 2018 Study of changes in groundwater resources has great importance on planning and management of sustainable water resources in any region. The goal of this study was trends and dominant period investigation in groundwater level data at monthly timescales ...
Farnaz Daneshvar Vousoughi, Reza Shaker
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On closed loop transient response system identification [PDF]
Modeling, Identification and Control, 2016 Some methods for transient closed loop step response system identification presented in the literature are reviewed. Interestingly some errors in a method published in the early 80's where propagated into a recently published method.
Christer Dalen, David Di Ruscio
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Tips for Statistical Tools for Research Methods in Exercise and Sport Sciences
Physical Education Theory and Methodology, 2023 Study purpose. The increasing amount of research in Exercise and Sport Sciences emphasized the use of increasingly heuristic statistical tools appropriate to the aim in terms of qualitative, quantitative, and qualitative-quantitative data.
Sara Aliberti +2 more
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Examining temporal features of BOLD-based cerebrovascular reactivity in clinical populations
Frontiers in Neurology, 2023 BackgroundConventional cerebrovascular reactivity (CVR) estimation has demonstrated that many brain diseases and/or conditions are associated with altered CVR.
Kayley-Jasmin Marchena-Romero +23 more
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Investigating Temporal and Spatial Precipitation Patterns in the Southern Mid-Atlantic United States
Frontiers in Climate, 2022 The investigation of regional vulnerability to extreme hydroclimatic events (e.g., floods and hurricanes) is quite challenging due to its dependence on reliable precipitation estimates.
Ishrat Jahan Dollan +2 more
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A Review of Shannon and Differential Entropy Rate Estimation
Entropy, 2021 In this paper, we present a review of Shannon and differential entropy rate estimation techniques. Entropy rate, which measures the average information gain from a stochastic process, is a measure of uncertainty and complexity of a stochastic process. We
Andrew Feutrill, Matthew Roughan
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Investigation of Parametric, Non-Parametric and Semiparametric Methods in Regression Analysis
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2022 Regression analysis is known as statistical methods applied to model and analyze the relationship between variables. Regression method can be examined as parametric, non-parametric and semiparametric regression methods.The parametric regression method ...
Esra Yavuz, Mustafa Şahin
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