Asymmetric interactions between different species of molecules have previously been demonstrated to result in self-organized ...

Generalized linear models (GLMs) are widely used for data analysis; however, their likelihood estimators can be sensitive to outliers. We propose new statistical models that allow robust inferences ...

Lawrence J. Christiano, Solving the Stochastic Growth Model by Linear-Quadratic Approximation and by Value-Function Iteration, Journal of Business & Economic Statistics, Vol. 8, No. 1 (Jan., 1990), pp ...

Deforming them is tricky and the deformations must be integrated into the actual model. That is, without something like a non-linear deformation space, as this paper talks about.

Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this ...

However, AI models are often used to find intricate patterns in data where the output is not always proportional to the input. For this, you also need non-linear thresholding functions that adjust ...

Object Details Author Qian, Song S Contents Basic Concepts -- Everglades Example -- Statistical Issues -- R -- What Is R? -- Getting Started with R -- R Commander -- Statistical Assumptions -- ...