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Multivariate Analysis of Mixed Data: The R Package PCAmixdata [PDF]
, 2017 Mixed data arise when observations are described by a mixture of numerical and categorical variables. The R package PCAmixdata extends standard multivariate analysis methods to incorporate this type of data.
Chavent, Marie +3 more
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On the mixed Cauchy problem with data on singular conics [PDF]
, 2007 We consider a problem of mixed Cauchy type for certain holomorphic partial differential operators whose principal part $Q_{2p}(D)$ essentially is the (complex) Laplace operator to a power, $\Delta^p$. We pose inital data on a singular conic divisor given
Author(s Ebenfelt +3 more
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The Fundamental Difference Between Qualitative and Quantitative Data in Mixed Methods Research
Forum: Qualitative Social Research, 2023 Mixed methods research is commonly defined as the combination and integration of qualitative and quantitative data. However, defining these two data types has proven difficult.
Judith Schoonenboom
doaj +1 more source
Improved Estimation of Human Lipoprotein Kinetics with Mixed Effects Models. [PDF]
PLoS ONE, 2015 Mathematical models may help the analysis of biological systems by providing estimates of otherwise un-measurable quantities such as concentrations and fluxes.
Martin Berglund +4 more
doaj +1 more source
mgm: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data [PDF]
, 2020 We present the R-package mgm for the estimation of k-order Mixed Graphical Models (MGMs) and mixed Vector Autoregressive (mVAR) models in high-dimensional data. These are a useful extensions of graphical models for only one variable type, since data sets
Haslbeck, Jonas M. B. +1 more
core +3 more sources
Existence of optimal boundary control for the Navier-Stokes equations with mixed boundary conditions [PDF]
, 2015 Variational approaches have been used successfully as a strategy to take advantage from real data measurements. In several applications, this approach gives a means to increase the accuracy of numerical simulations.
Guerra, Telma +2 more
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Parallel Coordinate Plots of Mixed-Type Data
Communications for Statistical Applications and Methods, 2008 Parallel coordinate plot of Inselberg (1985) is useful for visualizing dozens of variables, but so far the plot’s applicability is limited to the variables of numerical type. The aim of this study is to extend the parallel coordinate plot so that it can accommodate both numerical and categorical variables.
Il-Youp Kwak, Myung-Hoe Huh
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Advancing Spectral Clustering for Categorical and Mixed-Type Data: Insights and Applications
MathematicsThis study focuses on adapting spectral clustering, a numeric data-clustering technique, for categorical and mixed-type data. The method enhances spectral clustering for categorical and mixed-type data with novel kernel functions, showing improved ...
Cinzia Di Nuzzo
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BMC Genomics, 2022 Background Mixed models are used to correct for confounding due to population stratification and hidden relatedness in genome-wide association studies. This class of models includes linear mixed models and generalized linear mixed models.
Maryam Onifade +3 more
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Clustering of Mixed-Type Data Considering Concept Hierarchies
, 2019 Most clustering algorithms have been designed only for pure numerical or pure categorical data sets while nowadays many applications generate mixed data. It arises the question how to integrate various types of attributes so that one could efficiently group objects without loss of information.
Behzadi, S. +3 more
openaire +3 more sources