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hrtlFMC  

Half Replicate of Two Level Factorial Run Order with Minimum Level Changes
View on CRAN: Click here


Download and install hrtlFMC package within the R console
Install from CRAN:
install.packages("hrtlFMC")

Install from Github:
library("remotes")
install_github("cran/hrtlFMC")

Install by package version:
library("remotes")
install_version("hrtlFMC", "0.1.0")



Attach the package and use:
library("hrtlFMC")
Maintained by
Bijoy Chanda
[Scholar Profile | Author Map]
First Published: 2024-08-30
Latest Update: 2024-08-30
Description:
It is used to construct run sequences with minimum changes for half replicate of two level factorial run order. Experimenter can save time and resources by minimizing the number of changes in levels of individual factor and therefore the total number of changes. It consists of the function minimal_hrtlf(). This technique can be employed to any half replicate of two level factorial run order where the number of factors are greater than two. In Design of Experiments (DOE) theory, two level of a factor can be represented as integers e.g. - 1 for low and 1 for high. User is expected to enter total number of factors to be considered in the experiment. minimal_hrtlf() provides the required run sequences for the input number of factors.The output also gives the number of changes of each factor along with total number of changes in the run sequence. Due to restricted randomization the minimally changed run sequences of half replicate of two level factorial run order will be affected by trend effect. The output also provides the Trend Factor value of the run order. Trend factor value will lies between 0 to 1. Higher the values, lesser the influence of trend effects on the run order.
How to cite:
Bijoy Chanda (2024). hrtlFMC: Half Replicate of Two Level Factorial Run Order with Minimum Level Changes. R package version 0.1.0, https://cran.r-project.org/web/packages/hrtlFMC. Accessed 31 Mar. 2025.
Previous versions and publish date:
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Complete documentation for hrtlFMC
Functions, R codes and Examples using the hrtlFMC R package
Full hrtlFMC package functions and examples
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