Title: Probabilistic damage tolerance analysis for fatigue cracking of
Description: Using a sampling-based approach (either sequential importance sampling or explicit Monte Carlo), this package can be used to perform a probabilistic damage tolerance for aircraft structures. It can model a single crack, or two simultaneously growing fatigue cracks (the so-called continuing damage problem). With a single crack, multiple types of future repairs are possible.

Description: Implements Cragg-Donald (1993) <doi:10.1017/S0266466600007519> and Stock and Yogo (2005) <doi:10.1017/CBO9780511614491.006> tests for weak instruments in R.
Suggests: testthat (>= 3.0.0), knitr, MASS, rmarkdown
Packaged: 2021-01-05 20:31:53 UTC; beniamino

Description: Provides R routine for the multivariate

Title: Multivariate nonparametric Cramer-Test for the two-sample-problem
Description: Provides R routine for the so called two-sample Cramer-Test.
This not distribution free, nonparametric two-sample-test can be applied
on multivariate data as well as univariate data. It offers two
possiblities to approximate the critical value both of which are

Title: Multivariate nonparametric Cramer-Test for the
Description: Provides R routine for the so called two-sample
Cramer-Test.  This not distribution free, nonparametric
two-sample-test can be applied on multivariate data as well as
univariate data. It offers two possiblities to approximate the
critical value both of which are included in this package.
Packaged: Sun Jun 18 12:26:44 2006; carsten

Cramer-Test.  This nonparametric two-sample-test on equality
of the underlying distributions can be applied to
multivariate data as well as univariate data. It offers two
possibilities to approximate the critical value both of which

Title: Multivariate Nonparametric Cramer-Test for the

Authors@R: c(person("Thomas J.", "Leeper", email = "thosjleeper@gmail.com", role = c("aut", "cre")))
Description: Provides a data.frame listing of known data-only and data-heavy

Description: Provides a data frame listing of known data-only and data-heavy