Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces, NeurIPS 2021

A MATLAB project which applies the central limit theorem on PDFs and CDFs of different probability distributions.

PyPi package for modelling Probability distributions

[R] Statistical analysis of financial data conducted in R

deepIRF - A deep learning approach for reverse-broadening the instrumental response (IRF) in lifetime spectra

Generation of random samples using R

Saratov State University, CSIT. Discipline "pseudo-random numbers generators" (псевдослучайные генераторы, rus)

Go implementation of the Xoroshiro128++, Xoshiro256++, and Xoshiro512++ pseudo random number generators

A simulation of an ACPC Grading System Server where multiple computers process incoming tasks. The system handles exponential interarrival and service times with a FIFO queue mechanism and calculates key performance metrics like average delay time, waiting time, and time-based average queue length.

Raku package for statistical distributions and related random variates generations.

Closed-form MLE and Fisher information for exponential series systems with masked failure data. Includes theoretical results, proofs, and numerical validation.

Distinguish power-law and geometric (discrete exponential) distributions using RStan with bridge sampling

Elements related to the exponential distribution

Repository with statistical functions via Python

A pure-Python survival analysis framework that models cancer patient survival times using the exponential distribution, incorporating Monte Carlo simulation, goodness-of-fit testing, bootstrap inference, and publication-quality visualizations for academic and healthcare analytics.

M/M/1 model, exponential distribution, simulation model of manufacturing system

Lilliefors test with truncated exponential dithering

This is a set of Python Codes related to a basic data science Probability Course at a masters level.

Distributed M/M/C queue simulation using Apache Kafka as a FIFO buffer, Spring Boot producer/consumer with configurable parallel servers, Poisson load generation via k6, and full performance monitoring with Prometheus, Grafana, and PostgreSQL for analytical validation (Little’s Law, utilization, throughput, and queue length).