The problem of tting track data is transformed into a problem in antenna theory. This latter well-studied problem is characterized as an antenna array that is receiving a narrow band signal from multiple distant sources. The goal here is to count the number of sources and determine the angle of each source relative to the array. Similarly, the original problem of track tting is to count the num...

The whole correlation function of the intensity of scattered light is usually determined from a single realization of the photocurrent. As a result, the values of the correlation function at different delay times are not statistically independent. A standard least-squares fitting procedure is not optimal for an analysis of such data. However, the benefits of mathematically rigorous but highly n...

Subspace fitting has become a well known method to identify FIR Single Input Multiple Output (SIMO) systems, only resorting to second-order statistics. The main drawback of this method is its computational cost, due to the eigendecomposition of the sample covariance matrix. We propose a scheme that solves the subspace fitting problem without using the eigendecomposition of the cited matrix. The...

Standard Mobius transform evaluation formula for the Choquet integral is associated with the min-aggregation. However, several other aggregation operators replacing min operator can be applied, which leads to a new construction method for aggregation operators. All binary operators applicable in this approach are characterized by the 1-Lipschitz property. Among ternary aggregation operators all...

We describe a new framework for fitting jump models to a sequence of data. The key idea is to alternate between minimizing a loss function to fit multiple model parameters, and minimizing a discrete loss function to determine which set of model parameters is active at each data point. The framework is quite general and encompasses popular classes of models, such as hidden Markov models and piec...

In fitting atomic structures into EM maps, it often happens that the map corresponds to a different conformation of the structure. We have developed a new methodology to handle these situations that preserves the covalent geometry of the structure and allows the modeling of large deformations. The first goal is achieved by working in generalized coordinates (positional and internal coordinates)...

We show that the problems of approximating tensors and multivariate functions as a sums of (tensor) products of vectors/functions can be considered in a unified framework, thus exposing their common multilinear structure. We study the alternating least squares algorithm within this framework from the orthogonal projection and gradient perspectives. We then use these perspectives to study its co...

The problem of fitting ellipsoids occurs in many areas of science. It is useful in pattern recognition, particle physics, computer graphics, medical imaging of organs, and statistical error analysis. We describe an algorithm for finding an equation for a multi-dimensional ellipsoid fit to a distribution of discrete data points. In general, we find that the algorithm works well for fitting ellip...

Four sets of experimental data were investigated in terms of normal distribution and presence of outliers. The following sets of compound were investigated: blood-brain barrier partitioning (n=105), inhibitory activity of para-substituted aromatic sulfonamides (n=47), inhibition activity of taxoids (n=63), and estrogen receptor binding affinity of triphenilacrylonitriles (n=25). The normality o...

We perform a global Bayesian fit of the phenomenological minimal supersymmetric standard model (pMSSM) to current indirect collider and dark matter data. The pMSSM contains the most relevant 25 weak-scale MSSM parameters, which are simultaneously fit using ‘nested sampling’ Monte Carlo techniques in more than 15 years of CPU time. We calculate the Bayesian evidence for the pMSSM and constrain i...