Statistical Models and Methods for Data Science
This book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with data science. Numerous topics are covered, ranging from statistical inference and modelling to clustering and factorial methods, and from directional data analysis t...
保存先:
| 団体著者: | |
|---|---|
| その他の著者: | , , , , |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Cham :
Springer International Publishing : Imprint: Springer,
2023.
|
| 版: | 1st ed. 2023. |
| シリーズ: | Studies in Classification, Data Analysis, and Knowledge Organization,
|
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/978-3-031-30164-3 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
目次:
- Clustering financial time series by dependency
- The Homogeneity Index as a Measure of Interrater Agreement for Ratings on a Nominal Scale
- Hierarchical clustering of income data based on share densities
- Optimal Coding of High Cardinality Categorical Data in Machine Learning
- Bayesian Multivariate Analysis of Mixed data
- Marginals matrix under a generalized Mallows model based on the power divergence
- Time series clustering based on forecast distributions: an empirical analysis on production indices for construction
- Partial Reconstruction of Measures from Halfspace Depth
- Posterior Predictive Assessment of IRT Models via the Hellinger Distance: A Simulation Study
- Shapley Lorenz values for credit risk management
- A study of lack-of-fit diagnostics for models fit to cross-classified binary variables
- Robust Response Transformations for Generalized Additive Models via Additivity and Variance Stabilisation
- A Random-Coefficients Analysis with a Multivariate Random-Coefficients Linear Model
- Parsimonious mixtures of matrix-variate shifted exponential normal distributions.