Just as with other problems, there is a difference between randomization testing and bootstrap estimation. In the former, we are primarily interested in hypothesis testing, whereas the latter is ...
As a randomized variable in nonresponders and relapsed patients to assess its value in the choice of second-line therapy. At study entry, to ascertain whether the in vitro sensitivity to treatment ...
Just as with other problems, there is a difference between randomization testing and bootstrap estimation. In the former, we are primarily interested in hypothesis testing, whereas the latter is ...
1.) Wagstaff, K., Cardie, C., Rogers, S., & Schrödl, S. (2001, June). Constrained k-means clustering with background knowledge. In ICML (Vol. 1, pp. 577-584). 2 ...
CAR2.rmd: R code for randomization algorithm under the hypothetical case with ten covariates. CAR10.rmd: R code for randomization algorithm under the hypothetical case with two covariates. Farmer.rmd: ...
Abstract: This paper applies randomization theory to the problem of selecting software test cases for software systems and applications in order to overcome the hurdle of high cost in testing ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results