Cubic spline approximation (smoothing)
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Updated
Jul 15, 2024 - Python
Cubic spline approximation (smoothing)
DIVAnd performs an n-dimensional variational analysis of arbitrarily located observations
A Modern Fortran translation of the FITPACK package for curve and surface fitting
Python class for creating and optimizing quadratic and cubic Bezier curves and path smoothing implementation.
METAgenomic LONgitudinal Differential Abundance method
Smoothing algorithm and interpolation tool using cubic Bézier splines - reproduces Excel's smooth scatter plot
Computational Intelligence Packages (CIP) for Mathematica
Functional Data Analysis Group
Turn data points into a smooth Bézier curve in Dart
Cubic spline approximation (smoothing) in Rust
Short implementation of a EGRSS matrix format including an application example in smoothing spline fitting.
Im Rahmen der Mental Health Surveillance (MHS) am Robert Koch-Institut (RKI) werden für eine Auswahl an Indikatoren der psychischen Gesundheit von Erwachsenen basierend auf Surveydaten Zeitreihen bestehend aus gleitenden Drei-Monats-Schätzern und Glättungskurven berechnet. Dadurch sollen Entwicklungen in der psychischen Gesundheit der erwachsene...
Multivariate Normal Hermite-Birkhoff Uniform Smoothing Splines in Julia
Create a regression smoothing spline for a set of points.
MSc_dissertation_code
Please read the readme.md file
Performing different models on a dataset regarding National Park biodiversity and the number of visitors.
predicting house price using random forest model and smoothing spline model
Nonparametric regression examples with R and Python
Houses a series of projects I worked on for a course in Data Mining that I took in my Ph.D. Data Science program at UTEP in the Fall of 2022. Covers areas such as Regularized Logistic Regression, Optimization, Kernel Methods, PageRank, Kernel PCA, Association Rule Mining, Anomaly Detection, Parametric/Nonparametric Nonlinear Regression, etc.
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