Theoria motus corporum coelestium

@inproceedings{Gauss1981TheoriaMC,
  title={Theoria motus corporum coelestium},
  author={Carl Friedrich Gauss},
  year={1981}
}

Gauss on least-squares and maximum-likelihood estimation

  • J. Magnus
  • Mathematics
    SSRN Electronic Journal
  • 2021
Gauss’ 1809 discussion of least squares, which can be viewed as the beginning of mathematical statistics, is reviewed. The general consensus seems to be that Gauss’ arguments are at fault, but we

Sparse Relaxed Regularized Regression: SR3

TLDR
A new and highly effective approach for regularized regression, called SR3, to solve a relaxation of the regularized problem, which has three advantages over the state-of-the-art: solutions of the relaxed problem are superior with respect to errors, false positives, and conditioning.

Integer Ambiguity Resolution for Multi-GNSS and Multi-Signal Raw Phase Observations

TLDR
The carrier phase Integer Ambiguity Resolution (IAR) approach developed and implemented in the course of this work is based on the joint processing of multi-GNSS and multi-signal raw observations without forming any linear combinations or observation differences.

Systems of Structured Monotone Inclusions: Duality, Algorithms, and Applications

TLDR
A general primal-dual splitting algorithm for solving systems of structured coupled monotone inclusions in Hilbert spaces is introduced and its asymptotic behavior is analyzed, providing a flexible solution method applicable to a variety of problems beyond the reach of the state-of-the-art.

The latent distribution of a rating observed

ABSTRACT While extensive literature shows that the rating assigned by a critic or judge to a wine is one draw from a latent distribution, little has been published about the shape of that

Quantification of Kuramoto Coupling Between Intrinsic Brain Networks Applied to fMRI Data in Major Depressive Disorder

TLDR
The results indicate that the calculation of Ks can be a useful addition to standard methods of quantifying the brain's functional architecture and that a ground truth of parametric dependencies on artificial regressors can be recovered.

Degree and noise power estimation from noisy polynomial data via AR modelling

  • A. Nandi
  • Computer Science, Mathematics
    Digit. Signal Process.
  • 2021

Fixed Point Strategies in Data Science

TLDR
Fixed point strategies are seen to constitute a natural environment to explain the behavior of advanced convex optimization methods as well as of recent nonlinear methods in data science which are formulated in terms of paradigms that go beyond minimization concepts and involve constructs such as Nash equilibria or monotone inclusions.

AMERICAN ASSOCIATION OF WINE ECONOMISTS

While much literature shows that the ratings assigned by critics and judges to wines are stochastic, no author has yet proposed and tested a probability mass function (PMF) to describe the

Multi-Gaussian random variables

A generalization of the classic Gaussian random variable to the family of Multi- Gaussian (MG) random variables characterized by shape parameter M > 0, in addition to the mean and the standard
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