pyMOR - Model Order Reduction with Python
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Updated
Jun 5, 2024 - Python
pyMOR - Model Order Reduction with Python
Statistical analysis and visualization of state transition phenomena
R package for statistical inference using partially observed Markov processes
dynamic analysis of structural vibrations
The set of functions used for time series analysis and in forecasting.
KFAS: R Package for Exponential Family State Space Models
State-space, age-structured fish stock assessment model
A complete 6DOF helicopter simulation (physics engine + visualization)
Controllers designed to the 5MW NREL wind turbine using Simulink and Fast V8
Bayesian Inference of State Space Models
We are presenting a Bayesian local-level model and its extensions
Estimators for probabilities, entropies, and other complexity measures derived from data in the context of nonlinear dynamics and complex systems
sssMOR - Sparse State-Space and Model Order Reduction Toolbox
statespacer: State Space Modelling in R
Time varying vector autoregressive state space modeling of community interactions in a Bayesian framework
Controlling a nonholonomic robot to follow a trajectory with a modified PID Controller.
General state-space representation of linear, time-invariant systems in Golang
R codes and dataset for the estimation of the high-dimensional state space model proposed in the paper "A dynamic factor model approach to incorporate Big Data in state space models for official statistics" with Franz Palm, Stephan Smeekes and Jan van den Brakel.
An R package to extracts the trend and first derivative using a local linear model in state-space form and the Diffuse Kalman Filter
Rewriting a PID controller in state space form
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