Predicting weekly dengue cases for Iquitos and San Juan using Machine Learning algorithms
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Updated
Aug 28, 2017 - Jupyter Notebook
Predicting weekly dengue cases for Iquitos and San Juan using Machine Learning algorithms
Data analysis and model codes for DrivenData Projects.
Investigating Overdispersion's Effect on Modeling
Estimate the frequency and severity of claims to compute prior and posterior premiums. The GLM method is used with Poisson, Negative Binomial, Gamma, and Log-Norm Distribution.
R package for differential expression on count data with parameter bounds
🎓 Tidy tools for academics
Can features of the built environment be used to predict the locations of pedestrian crashes at the street level in Uptown Charlotte, North Carolina?
Batch effect adjustment based on negative binomial regression for RNA sequencing count data
Negative Binomial Additive Model for RNASeq Data
Using the Poisson Regression Model and NB Regression Model to predict number of rental bikes.
MSDS 410 Data Modeling for Supervised Learning (R)
A comparison between Poisson regression, quasi-Poisson regression, and negative binomial regression for overdispersed count data.
Mixed Poisson Regression for Overdispersed Count Data
Assignment for Advanced Predictive Modeling for MSc Data Analytics
Multi-sample somatic variant caller
Quick Guide for Modelling Count Data in A Multilevel Framework
Statistical Analysis about cancer incidence in Modena hospital.
Companion repository to Lause, Berens & Kobak (2021): "Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data", Genome Biology
Evaluating proposed CGAN-EB method in simulation enironment
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