tuningBIC {FARDEEP} | R Documentation |
Tuning parameter k in function alts using Bayesian Information Criterion (BIC) with some adjustment.
Description
Tuning parameter k in function alts using Bayesian Information Criterion (BIC) with some adjustment.
Usage
tuningBIC(x, y, alpha1 = 0.1, alpha2 = 1.5, up = 10, low = 1,
nn = TRUE, intercept = TRUE, lognorm = TRUE)
Arguments
x |
input matrix of predictors with n rows and p columns. |
y |
input vector of dependent variable with length n. |
alpha1 |
parameter used to adjust the upper bound of outliers. Take value from 0 to 1, default 0.1. |
alpha2 |
parameter used to adjust the lower bound of outliers. Take value larger than 1, default 1.5. |
up |
upper bound of parameter k in function alts, default 10. |
low |
lower bound of parameter k in function alts, default 1. |
nn |
whether coefficients are non-negative, default TRUE. |
intercept |
whether intercept is included in model, default TRUE. |
lognorm |
whether noise is log-normal distributed, default TRUE. |
Value
k: tuning result of parameter k for function alts.
Author(s)
Yuning Hao, Ming Yan, Blake R. Heath, Yu L. Lei and Yuying Xie
References
Yuning Hao, Ming Yan, Blake R. Heath, Yu L. Lei and Yuying Xie. Fast and Robust Deconvolution of Tumor Infiltrating Lymphocyte from Expression Profiles using Least Trimmed Squares. <doi:10.1101/358366>
Examples
library(FARDEEP)
samp = sample.sim(n = 500, p = 20, sig = 1, a1 = 0.1, a2 = 0.2, nn = TRUE, intercept = TRUE)
k = tuningBIC(samp$x, samp$y, lognorm = FALSE)