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Nonparametric statistics
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Related lectures (32)
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Geometry: Introduction to Euclidean Elements
Explores the historical evolution of geometric instruments and the transition to modern CAD software for architectural design.
Parameter Estimation of SDEs with Linear Response Theory
Explores parameter estimation of SDEs using Linear Response Theory and covers challenges, examples, algorithms, and convergence.
Multiple Hypothesis Testing
Explores the challenges of multiple hypothesis testing and non-parametric estimation techniques.
Bivariate Maxima: Parametric Models and Distributions
Explores bivariate maxima, parametric models, distributions, and dependence functions in statistics.
Non-parametric regression for networks
Explores non-parametric regression for networks, covering object data analysis, network graphs, extrinsic distances, and practical projections.
Geometric Structures: Stereotomy
Explores traditional stone cutting and assembly techniques, geometric modeling, and the historical development of projective geometry in stereotomy.
Signal Models and Methods: Parametric vs Nonparametric
Provides an overview of signal models and methods in statistical signal processing.
Special Families of Models
Explores completeness, minimal sufficiency, and special statistical models, focusing on exponential and transformation families.
Descriptive Statistics: Hypothesis Testing
Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.
Nonparametric Estimation: Empirical Likelihood Approach
Explores nonparametric estimation using the empirical likelihood approach and discusses the computation of probabilities and empirical estimation.
Hypothesis Testing and Non-Parametric Regression
Covers worked examples on hypothesis testing and non-parametric regression.
Poisson Process Approach
Explores the Poisson process approach in extreme value analysis, emphasizing component-wise transformations and likelihood functions for extreme events.
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