funGP {DSWE} | R Documentation |
Function comparison using Gaussian Process and Hypothesis testing
funGP(
datalist,
xCol,
yCol,
confLevel = 0.95,
testset,
limitMemory = TRUE,
opt_method = "nlminb",
sampleSize = list(optimSize = 500, bandSize = 5000),
rngSeed = 1
)
datalist |
A list of data sets to compute a function for each of them |
xCol |
A numeric or vector stating the column number of covariates |
yCol |
A numeric value stating the column number of target |
confLevel |
A single value representing the statistical significance level for constructing the band |
testset |
Test points at which the functions will be compared |
limitMemory |
A boolean (True/False) indicating whether to limit the memory use or not. Default is true. If set to true, 5000 datapoints are randomly sampled from each dataset under comparison for inference. |
opt_method |
A string specifying the optimization method to be used for hyperparameter estimation. Current options are: |
sampleSize |
A named list of two integer items: |
rngSeed |
Random seed for sampling data when |
a list containing :
muDiff - A vector of pointwise difference between the predictions from the two datasets (mu2- mu1)
mu1 - A vector of test prediction for first data set
mu2 - A vector of test prediction for second data set
band - A vector of the allowed statistical difference between functions at testpoints in testset
confLevel - A numeric representing the statistical significance level for constructing the band
testset - A matrix of test points to compare the functions
estimatedParams - A list of estimated hyperparameters for GP
Prakash, A., Tuo, R., & Ding, Y. (2020). "Gaussian process aided function comparison using noisy scattered data." arXiv preprint arXiv:2003.07899. <https://arxiv.org/abs/2003.07899>.
datalist = list(data1[1:100,], data2[1:100, ])
xCol = 2
yCol = 7
confLevel = 0.95
testset = seq(4,10,length.out = 20)
function_diff = funGP(datalist, xCol, yCol, confLevel, testset)