Nonparametric statistics

Related lectures (32)

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Explores the historical evolution of geometric instruments and the transition to modern CAD software for architectural design.

Explores parameter estimation of SDEs using Linear Response Theory and covers challenges, examples, algorithms, and convergence.

Explores the challenges of multiple hypothesis testing and non-parametric estimation techniques.

Explores bivariate maxima, parametric models, distributions, and dependence functions in statistics.

Explores non-parametric regression for networks, covering object data analysis, network graphs, extrinsic distances, and practical projections.

Explores traditional stone cutting and assembly techniques, geometric modeling, and the historical development of projective geometry in stereotomy.

Provides an overview of signal models and methods in statistical signal processing.

Explores completeness, minimal sufficiency, and special statistical models, focusing on exponential and transformation families.

Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.

Explores nonparametric estimation using the empirical likelihood approach and discusses the computation of probabilities and empirical estimation.