Results 71 to 80 of about 615,565 (289)

On the Covariance of the Community Matrix [PDF]

Ecology, 1972
A clarification of the meaning of the covariance of the community matrix is presented along with calculating equations for both the mean species covariance and the covariance of the row and column means. A brief discussion of α selection and its determination of the covariance is given, followed by table for determining the expected number of species ...
openaire   +2 more sources

Regularized Tapered Sample Covariance Matrix

IEEE Transactions on Signal Processing, 2022
Covariance matrix tapers have a long history in signal processing and related fields. Examples of applications include autoregressive models (promoting a banded structure) or beamforming (widening the spectral null width associated with an interferer).
Breloy, Arnaud, Ollila, Esa
openaire   +4 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

The Effects of Data Imputation on Covariance and Inverse Covariance Matrix Estimation

IEEE Access
Various data analysis techniques and procedures (correlation heatmap, linear discriminant analysis, quadratic discriminant analysis) rely on the estimation of the covariance matrix or its inverse (the precision matrix).
Tuan L. Vo, Quan Huu Do, Thu Nguyen, Pal Halvorsen, Michael A. Riegler, Binh T. Nguyen   +5 more
doaj   +1 more source

On the repeated inversion of a covariance matrix

CoRR, 2017
In many cases, the values of some model parameters are determined by maximising the likelihood of a set of data points given the parameter values. The presence of outliers in the data and correlations between data points complicate this procedure. An efficient procedure for the elimination of outliers is presented which takes the correlations between ...
openaire   +2 more sources

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Improved Large Dynamic Covariance Matrix Estimation With Graphical Lasso and Its Application in Portfolio Selection

IEEE Access, 2020
The estimation of the large and high-dimensional covariance matrix and precision matrix is a fundamental problem in modern multivariate analysis. It has been widely applied in economics, finance, biology, social networks and health sciences. However, the
Xin Yuan, Weiqin Yu, Zhixiang Yin, Guoqiang Wang   +3 more
doaj   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Portfolio Optimization Using a Consistent Vector-Based MSE Estimation Approach

IEEE Access, 2022
This paper is concerned with optimizing the weights of the global minimum-variance portfolio (GMVP) in high-dimensional settings where both observation and population dimensions grow at a bounded ratio. Optimizing the GMVP weights is highly influenced by
Maaz Mahadi, Tarig Ballal, Muhammad Moinuddin, Ubaid M. Al-Saggaf   +3 more
doaj   +1 more source

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

Advanced Engineering Materials, EarlyView.
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova, Steffen Brinckmann, Ruth Schwaiger   +2 more
wiley   +1 more source