Regression is a method to estimate parameters in mathematical models of biological systems from experimental data. To ensure the validity of a model for a given data set, pre-regression and post ...

Using integrated modeling solutions to implement model-driven data management and development can help organizations share knowledge effectively and with minimum effort. It will certainly produce ...

Michael Vogt, Oliver Linton, Classification of non-parametric regression functions in longitudinal data models, Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 79, ...

Technological Innovation: The Significance of the Data Analysis Agent Evaluation Patent ...

Missing data is a major issue in many applied problems, especially in the biomedical sciences. We review four common approaches for inference in generalized linear models (GLMs) with missing covariate ...

One of the most important steps in desiging a database is establishing the data model. Part one of a two-part article describes how to create a logical model.

Discover what black box models are, their applications in finance and investing, and examples of how they drive ...

Data poisoning is a type of attack that involves tampering with and polluting a machine learning model's training data, impacting the model's ability to produce accurate predictions.