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#

sampling-distribution

Here are 50 public repositories matching this topic...

Sampling particles on a hypersurface with local event-by-event account of energy, momentum, baryon number, strangeness and charge conservation.

  • UpdatedJul 25, 2023
  • C++

An open-source JAX-based statistical sampling toolkit 🧪

  • UpdatedJun 8, 2024
  • Python

Simulation Methods in Econometrics: Theory and Applications in MATLAB is an open-source textbook that aims to bridge the gap between econometric theory and the practical use of simulation techniques. It emphasizes intuition, reproducibility, and accessibility.

  • UpdatedNov 10, 2025
  • MATLAB

Analysis of mock A/B Test Results by an e-commerce company. Application of probability, hypothesis testing, sampling distribution, two-sample z-test, and logistic regression to determining whether the company should implement the new web page it developed to increase users' conversion rate

  • UpdatedMar 23, 2019
  • HTML

Demonstrates reverse annealing on D-Wave quantum computers.

  • UpdatedApr 3, 2025
  • Jupyter Notebook

Package provides python implementation of statistical inference engine

  • UpdatedJun 16, 2017
  • Python

Use bootstrap resampling to estimate the sampling distribution of a statistic

  • UpdatedSep 19, 2025
  • Python

Tutorial: A simple GAN to generate samples from Gaussian distribution

  • UpdatedMay 5, 2020
  • Jupyter Notebook

This code can be used to reproduce the results in our paper ``A Control Approach for Nonlinear Stochastic State Uncertain Systems with Probabilistic Safety Guarantees''.

  • UpdatedMar 30, 2024
  • Jupyter Notebook

A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.

  • UpdatedJun 21, 2021
  • HTML

Demonstrate techniques that help quantum applications find better, more robust solutions by comparing two generations of D-Wave 2000Q QPUs.

  • UpdatedApr 4, 2025
  • Python

This takes any Pandas or Dask dataframe and returns a resampled Dask dataframe simulating the sampling distribution of your data in one line of code. This is like the rep_sample_n() function from the infer package in R, but on steroids and made for quickly simulating a large number of replicate samples and even with a large number of observation…

  • UpdatedNov 23, 2020
  • Jupyter Notebook

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