GSoC_mcmcse_tests_2021

Tests for the GSoC project 'Critical efficiency improvements of mcmcse', under R stats

Test 1

Easy: (1) Download the mcmcse package from CRAN and use the function ess on a vector foo of length 1e4 randomly drawn from a standard normal distribution.
(2) Make a random matrix of size 10 x 10 and produce only the eigenvalues of the matrix.

Test 2

• Medium: Implement an efficiency profile of the batchSize() function using profvis. Do this for varying sizes of input matrices.

Test 3

• Hard: Write a code for a random walk Metropolis-Hastings algorithm to sample from a 100 dimensional standard normal Gaussian distribution. Focus on efficient implementation of this code. (2) Calculate the effective sample size as described in this paper in a way that is numerically stable, and does not utilize any inbuilt functions. Make sure you write your own function for this.