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

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.

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

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

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.

Repository with statistical functions via Python

Elements related to the exponential distribution

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

Teme Probabilitati si Statistica (PS), Anul 2, Semestrul 1, Facultatea de Matematica si Informatica, Universitatea din Bucuresti

Johns Hopkins University Bloomberg School of Public Health: Data Science Specialization Program: Statistical Inference Course Peer Review project repo: date created 60806

code for printing stem and leaf plots

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).

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

This Shiny application allows users to visualize the cumulative distribution functions (CDFs) of a random variable 𝑥 following one of the selected probability distributions: Standard Normal Distribution - 𝑁(0,1) , General Normal Distribution - 𝑁(𝜇,𝜎^2) or Exponential Distribution - 𝐸𝑥𝑝(𝜆). Users can select the distribution's parameters.