cmstatr package provides functions for performing statistical
analysis of composite material data. The statistical methods implemented
are those described in CMH-17-1G. This package
focuses on calculating basis values (lower tolerance bounds) for
material strength properties, as well as performing the associated
diagnostic tests. Functions are also provided for testing for
equivalency between alternate samples and the “qualification” or
Additional details about the package are available in the paper by Kloppenborg (2020, https://doi.org/10.21105/joss.02265).
cmstatr from CRAN, simply run:
If you want the latest development version, you can install it from
devtools. This will also install the dependencies
required to build the vignettes. Optionally, change the value of the
ref to install
cmstatr from a different branch of the
install.packages(c("devtools", "rmarkdown", "dplyr", "tidyr")) devtools::install_github("cmstatr/cmstatr", build_vignettes = TRUE, ref = "master", build_opts = c("--no-resave-data", "--no-manual"))
To compute a B-Basis value from an example data set packaged with
cmstatr you can do the following:
library(dplyr) library(cmstatr) carbon.fabric.2 %>% filter(test == "FC") %>% filter(condition == "RTD") %>% basis_normal(strength, batch) #> #> Call: #> basis_normal(data = ., x = strength, batch = batch) #> #> Distribution: Normal ( n = 18 ) #> B-Basis: ( p = 0.9 , conf = 0.95 ) #> 76.88082
For more examples of usage of the
cmstatr package, see the tutorial
vignette, which can be viewed
online, or can
be loaded as follows, once the package is installed:
There is also a vignette showing some examples of the types of graphs that are typically produced when analyzing composite materials. You can view this vignette online, or you can load this vignette with:
This package expects
tidy data. That is,
individual observations should be in rows and variables in columns.
Where possible, this package uses general solutions. Look-up tables are avoided wherever possible.
If you’ve found a bug, please open an issue in this repository and describe the bug. Please include a reproducible example of the bug. If you’re able to fix the bug, you can do so by submitting a pull request.
If your bug is related to a particular data set, sharing that data set will help to fix the bug. If you cannot share the data set, please strip any identifying information and optionally scale the data by an unspecified factor so that the bug can be reproduced and diagnosed.
cmstatr are always welcomed. For small changes
(fixing typos or improving the documentation), go ahead and submit a
pull request. For more significant changes, such as new features, please
discuss the proposed change in an issue first.
R CMD checkpasses with no errors, warnings or notes
testthat. If your contribution fixes a bug, then the test(s) that you add should fail before your bug-fix patch is applied and should pass after the code is patched.
NEWS.mdbelow the current development version
Testing is performed using
testthat. Edition 3 of that package is used
and parallel processing enabled. If you wish to use more than two CPUs,
set the environment variable
TESTTHAT_CPUS to the number of CPUs that
you want to use. One way of doing this is to create the file
with the following contents. This file is ignored both by
git and also
Sys.setenv(TESTTHAT_CPUS = 8)
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