This is a preview. Log in through your library . Abstract The analysis of cross-classified discrete data using log-linear models is now as commonplace as the analysis of continuous data using linear ...
In a variety of problems involving models from genetics, latent-class analysis, and missing data, I apply a log-linear model to an indirectly observed frequency table. Current algorithms for ...
James Chen, CMT is an expert trader, investment adviser, and global market strategist. Thomas J. Brock is a CFA and CPA with more than 20 years of experience in various areas including investing, ...
Abstract: To optimize the dispatch of batteries, a model is required that can predict the state of energy (SOE) trajectory for a chosen open-loop power schedule to ensure admissibility (i.e., that ...
This paper studies the theoretical underpinnings of log-linear models of relative asset demand. It shows that log-linearity provides a poor approximation - in both a global and local sense - to asset ...
We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
Abstract: Log parsing is a critical step that transforms unstructured log data into structured formats, facilitating subsequent log-based analysis. Traditional syntax-based log parsers are efficient ...
Julia Kagan is a financial/consumer journalist and former senior editor, personal finance, of Investopedia. Andy Smith is a Certified Financial Planner (CFP®), licensed realtor and educator with over ...
Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. In early-stage estrogen receptor-positive (ER ...
Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. Expression of a psoriasis-associated ...
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