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Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests - Chapman & Hall / CRC Monographs on Statistics and Applied Probability Liang, Faming (Purdue University, West Lafayette, IN)
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Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests - Chapman & Hall / CRC Monographs on Statistics and Applied Probability
Liang, Faming (Purdue University, West Lafayette, IN)
This book provides a general framework for learning sparse graphical models with conditional independence tests. It includes complete treatments for Gaussian, Poisson, multinomial, and mixed data; unified treatments for covariate adjustments, data integration, and network comparison.
149 pages, 12 Tables, black and white; 8 Line drawings, color; 7 Line drawings, black and white; 8 I
| Mediji | Grāmatas Hardcover Book (Grāmata ar cieto muguriņu un vāku) |
| Izlaists | 2023. gada 2. augusts |
| ISBN13 | 9780367183738 |
| Izdevēji | Taylor & Francis Ltd |
| Lapas | 130 |
| Izmēri | 242 × 162 × 14 mm · 348 g |
| Valoda | Angļu |
