Work from MSU course STT 461 - Computer algorithms for evaluation, simulation and visualization.
BigData_Kurtansky_Nick_STT461_project_20180426.Rmd: Simulating of a Sure Independent Sampling on a "big data" set. In Part 1, I produced data sets whose true response signal to varibles are known, and then calculated the MMS, which is the median number of variables needed in the model in order to identify all true signals. In Part 2, I identify the top 10 variables contributing to a string of cancer from a big data set using SIS.
Kurtansky_Nick1.Rmd: Simple manipulation of datasets
Kurtansky_Nick2.Rmd: Inverse CDF method for random number generation and writing functions for simple simulations
Kurtansky_Nick3.Rmd: Rejection sampling and Monte Carlo estimation and importance sampling
Kurtansky_Nick4.Rmd: Regression modelling and bootstrapping
Kurtansky_Nick5.Rmd: Permutation testing