Taguchi Design Analysis in R скачать в хорошем качестве

Taguchi Design Analysis in R

The Taguchi’s Design of Experiment is a fractional factorial design that significantly minimize the number of experiments. In order to carry out in R, the package qualityTools is needed that is now no longer available in CRAN but can be availed from GitHub. In order to install package from GitHub, the R-package devtools is needed. The qualityTools can be installed using codes as under: install.packages("devtools") library(devtools) install_github("cran/qualityTools") The different types of experimental designs are “L4_2” for three two-level factors “L8_2” for seven two-level factors “L9_3” for four three-level factors “L12_2” for 11 two-level factors “L16_2” for 16 two-level factors “L16_4” for 16 four-level factors “L18_2_3” for one two-level and seven three-level factors “L25_5” for six five-level factors “L27_3” for 13 three-level factors “L32_2” for 32 two-level factors “L32_2_4” for one two-level factor and nine four-level factors “L36_2_3_a” for 11 two-level factors and 12 three-level factors “L36_2_3_b” for three two-level factors and 13 three-level factors “L50_2_5” for one two-level factor and eleven five-level factors “L8_4_2” for one four-level factor and four two-level factors “L16_4_2_a” for one four-level factor and 12 two-level factors “L16_4_2_b” for two four-level factors and nine two-level factors “L16_4_2_c” for three four-level factors and six two-level factors “L16_4_2_d” for five four-level factors and two two-level factors “L18_6_3” for one six-level factors and six three-level factors. Link for codes: https://drive.google.com/file/d/1lsno...