negative-binomial

Companion repository to Lause, Berens & Kobak (2021): "Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data", Genome Biology

Probabilistic outlier identification for bulk RNA sequencing data

NewWave

Various Fortran codes

Code for fitting a negative binomial distribution in Python

Negative binomial distributed pseudorandom numbers.

Geographically Weighted Negative Binomial Regression in Python - local spatial modeling for over dispersed count data.

Research code and reproducibility materials for a mobility-informed SIR model using subway ridership data, particle smoothing, and mobility-reduction scenarios to evaluate influenza transmission and the instantaneous reproduction number.

High-precision ribosome pause detection tool utilizing Negative Binomial modeling to optimize Z-scores and extract ML-ready contextual features from Ribo-seq data.

The DOTNB repository is a collection of code files that implement DOTNB across several programming languages. The DOTNB is the distribution for the Difference Of Two Negative Binomial distributions, i.e., Z=X-Y ~ DOTNB (λ_1,λ_2,p_1,p_2), where X ~ NB(λ_1,p_1 ) and Y ~ NB(λ_2,p_2 ).

Create an iterator for generating pseudorandom numbers drawn from a negative binomial distribution.

Create an array containing pseudorandom numbers drawn from a negative binomial distribution.

RNS-Seq Count Model Explorer

The DEGage2 package works to identify differentially expressed genes (DEGs) on bulk RNA-seq data through utilization of DOTNB

DEGage is a novel model-based method for gene differential expression analysis between two groups of scRNA-seq count data. It employs a novel family of discrete distributions for describing the difference of two NB distributions (named DOTNB).

Final project in Safety Management: analytics and predictive modeling for occupational incidents. Includes EDA, logistic regression, Poisson/Negative Binomial with overdispersion checks, ROC/AUC, and prediction exercises.

Applied Multiple Systems Estimation (MSE) econometric framework in R & Python reconstructing hidden populations of modern slavery victims across UK, Netherlands, New Orleans, and Kosovo testbeds via Negative Binomial and Quasi-Poisson GLMs.

Optional presentation for the "Sistemi Complessi" course.

Regional Consistency Probability for Single-Arm Multi-Regional Clinical Trials

Slides sobre modelos de regressão poisson e binomial negativa inflacionadas de zeros