Basic scatter plots with overlayed linear fit and ideal trend lines for visualizing estimator performance
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Updated
Jul 4, 2021 - Julia
Basic scatter plots with overlayed linear fit and ideal trend lines for visualizing estimator performance
Simple methods to solve generalized method of moments (GMM) estimation.
PERK: Parameter Estimation via Regression with Kernels
Implements Poisson fixed effects regression and robust standard errors from Wooldridge (1999) in Julia. The implementation should be faster than GLM.jl with many fixed effects.
Inverse distance estimation solver for the GeoStats.jl framework
Estimator of Indirect Measurement Errors, written in Julia.
Geostatistical estimation solvers for the GeoStats.jl framework
Leveraging the full dimensionality of single-cell transcriptomics (among other things!)
Built-in solvers for the GeoStats.jl framework
Locally weighted regression solver for the GeoStats.jl framework
Methods for M-estimation of statistical models
Real time estimation of epidemic Effective Reproduction Number for Luxembourg
WORK-IN-PROGRESS Solve and estimate heterogenous agent models with sequence-space Jacobians
package for Bayesian and classical estimation and inference based on statistics that are filtered through a trained neural net
Jackknife resampling and estimation in Julia
Solve many kinds of least-squares and matrix-recovery problems
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
State estimation, smoothing and parameter estimation using Kalman and particle filters.
System Identification toolbox, compatible with ControlSystems.jl
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