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Entropy-Based Uncertainty Quantification in Linear Consecutive k-out-of-n:G Systems via Cumulative Residual Tsallis Entropy [PDF]
EntropyQuantifying uncertainty in complex systems is a central problem in reliability analysis and engineering applications. In this work, we develop an information-theoretic framework for analyzing linear consecutive k-out-of-n:G systems using the cumulative ...
Boshra Alarfaj +2 more
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A Simple Nonparametric Least-Squares-Based Causal Inference for Heterogeneous Treatment Effects. [PDF]
J Nonparametr StatEstimating treatment effects is a common practice in making causal inferences. However, it is a challenging task for observational studies because the underlying models for outcome and treatment assignment are unknown.
Zhang Y +5 more
europepmc +2 more sources
STATISTICAL INFERENCE FOR MEAN FUNCTIONS OF COMPLEX 3D OBJECTS. [PDF]
Stat SinThe use of complex three-dimensional (3D) objects is growing in various applications as data collection techniques continue to evolve. Identifying and locating significant effects within these objects is essential for making informed decisions based on ...
Wang Y +4 more
europepmc +2 more sources
A review on asymptotic inference in stochastic differential equations with mixed effects [PDF]
Japanese Journal of Statistics and Data Science, 2021 This paper is a survey of recent contributions on estimation in stochastic differential equations with mixed effects. These models involve N stochastic differential equations with common drift and diffusion functions but random parameters that allow for ...
M. Delattre
semanticscholar +2 more sources
Nonparametric inference for additive models estimated via simplified smooth backfitting [PDF]
Annals of the Institute of Statistical Mathematics, 2022 We investigate hypothesis testing in nonparametric additive models estimated using simplified smooth backfitting (Huang and Yu, Journal of Computational and Graphical Statistics, 28(2), 386–400, 2019).
S. Chatla
semanticscholar +1 more source
A Time-Varying Coefficient Double Threshold GARCH Model with Explanatory Variables
Axioms, 2023 In this article, we consider the nonparametric inference for the time-varying coefficient double-threshold generalized autoregressive conditional heteroscedastic models.
Tongwei Zhang +3 more
doaj +1 more source
Mathematics, 2023 This paper studies the estimation and inference of a partially linear varying coefficient spatial autoregressive panel data model with fixed effects. By means of the basis function approximations and the instrumental variable methods, we propose a two ...
Sanying Feng, Tiejun Tong, Sung Nok Chiu
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Regression Analysis of Dependent Current Status Data with Left Truncation
Mathematics, 2023 Current status data are encountered in a wide range of applications, including tumorigenic experiments and demographic studies. In this case, each subject has one observation, and the only information obtained is whether the event of interest happened at
Mengyue Zhang +4 more
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Nonparametric Estimation of Multivariate Copula Using Empirical Bayes Methods
Mathematics, 2023 In the fields of finance, insurance, system reliability, etc., it is often of interest to measure the dependence among variables by modeling a multivariate distribution using a copula.
Lu Lu, Sujit Ghosh
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Statistical Papers, 2023 Nonparametric confidence distributions estimate statistical functionals by a distribution function on the parameter space, instead of the classical point or interval estimators.
Jonas Beck, A. Bathke
semanticscholar +1 more source