Data Analysis with Bootstrap Estimation in R
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Updated
Aug 18, 2024 - R
Data Analysis with Bootstrap Estimation in R
Random vectors: marginal and conditional distributions. Normal, t-distribution, Chi-square and F-distribution... AND A LOT MORE.
Repository for the OpenMx Structural Equation Modeling package
Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction
Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood
Targeted inference (R package) https://kkholst.github.io/targeted/
Bias reduction in quasi likelihood estimation
Resource Selection (Probability) Functions for Use-Availability Data in R
Framework for estimating parameters and the empirical sandwich covariance matrix from a set of unbiased estimating equations (i.e. M-estimation) in R.
An R package for maximum likelihood estimation of univariate densities.
📈 📉 📈 📈 📉 Multisignal GMWM estimation and model selection for IMU
The repo is presented for estimation of the price bonds using vasicek algorithm using R.
Hierarchical Bayesian Models to assess Learning and Guessing Strategies in Reinforcement Learning
Estimation Approach to Statistical Inference [R Package]
Complexity of Infection Estimation with Allele Frequencies
An example of using Bayesian linear regression to perform estimation for the duration of software projects.
Correspondence to Lancet regarding the article by Santos-Burgoa and colleagues (2018)
Undergraduate Final Project on behalf of Radisha Fanni Sianti
R code for estimation of latent class logit model with aggregate data
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