R
Projects with this topic
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I worked as a research assistant at the Chair of Computational Cognitive Neuroscience (UZH) from 2017 to 2020, contributing to a project led by Prof. Dr. Dr. Dominik R. Bach at the Bachlab.
My tasks included:
•Developing an online experiment focused on approach-avoidance behavior. •Creating an online game as part of the experiment. •Hosting MySQL servers and conducting statistical analyses of the data using R.
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I worked as a research assistant at the Chair of Computational Cognitive Neuroscience (UZH) from 2017 to 2020, contributing to a project led by Prof. Dr. Dr. Dominik R. Bach at the Bachlab.
My tasks included:
•Developing an online experiment focused on approach-avoidance behavior. •Creating an online game as part of the experiment. •Hosting MySQL servers and conducting statistical analyses of the data using R.
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Materials and resources for the teaching unit "Morphometrics with R" (University of Bordeaux, Summer School, 2024). Website.
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Draft for a medium online course (moc) on using R for data analysis in the psychological sciences and related fields
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📦 camtrapmonitoring is an R package for planning and evaluating camera trap surveys and (soon) estimating wildlife density. Formerly named {wildcam}.Updated -
Documentos referentes al curso de Introducción a la bioestadística y programación:
Hojas de cálculo Bioestadística Programas bioinformáticos Bases de datos biosanitarias Lenguajes de programación Lenguaje de programación RUpdated -
An R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with antibiotic data by using evidence-based methods.
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Mirrored to https://gitlab.b-data.ch/r/best-practice.
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Mirrored to https://gitlab.b-data.ch/r/template.
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Deployment URL: https://r.b-data.ch/plumber-template/__docs__/
Mirrored to https://gitlab.b-data.ch/r/api/plumber-template.
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Fit parametric models for time-to-event data that show an initial 'incubation period', i.e., a variable phase where the hazard is zero. The delayed Weibull distribution serves as the foundational data model. The specific method of MPSE (maximum product of spacings estimation) or different variants of MLE (maximum likelihood estimation) are implemented for parameter estimation. Bootstrap confidence intervals for parameters and significance tests in a two group setting are provided as well.
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