The 'Semiparametric regression' course at the Institute of Mathematics (University of Wrocław).
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Updated
Aug 27, 2020 - R
The 'Semiparametric regression' course at the Institute of Mathematics (University of Wrocław).
Version controlled, editable source for the genetic group 'How To': Wolak & Reid (2017) Journal of Animal Ecology, Appendix S6
This repo is for linear models and linear mixed models using Python.
Semantic model of LMM analysis
This repository contains the code and reports for the statistical analysis of BIXI Montreal's bike-sharing system data. The analysis focuses on understanding the factors that influence trip duration, revenue, and overall usage based on the 2021 season's data.
[Done] Randomized clinical trial of Plasma solution A vs. Normal saline for fluid resuscitation in post-cardiac arrest patients
Conduct one-way and multi-way anova in Julia with MixedModels.jl
QPCRinR is a powerful web app for the analysis of RT-qPCR data with Linear Mixed Models. It is designed for testing multiple factors and combine experiments in a simple and interactive manner.
Generalized fiducial inference for linear mixed models
[DONE] To compare responses related to sleep/feelings between the Jang Bogo station and the King Sejong station
Materials associated with the webinar, "Higher Learning: Hierarchical Linear Models"
Data Analysis for "All-or-none neural mechanisms underlying visual categorisation: evidence of the N170".
SAMUEL-ROSA, A. et al. Do more detailed environmental covariates deliver more accurate soil maps? Geoderma, v. 243–244, p. 214–227, maio 2015.
Official implementation of Capturing Between-Tasks Covariance and Similarities Using Multivariate Linear Mixed Models [EJS 2020]
Robust estimation using heavy-tailed distributions
unfold+mixed models = unmixed | alpha version!
Curated list of the sources about multilevel models
Matlab and shell scripts associated with the paper "Correcting datasets leads to more homogeneous early 20th century sea surface warming" by Duo Chan, Elizabeth C. Kent, David I. Berry, and Peter Huybers.
Approximate Ridge Linear Mixed Models (arLMM)
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