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Practical applications of sparse modeling
"Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and comput…
- Edition
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- ISBN/ISSN
- 9780262325325
- Collation
- 1 online resource (xii, 249 pages).
- Series Title
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- Call Number
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State-space models with regime switching :classical and Gibbs-sampling approa…
"Both state-space models and Markov-switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-…
- Edition
- -
- ISBN/ISSN
- 9780585087160
- Collation
- 1 online resource (xii, 297 pages) :illustrations
- Series Title
- -
- Call Number
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