`R/basis.R`

`k_factor_normal.Rd`

The factors returned by this function are used when calculating basis
values (one-sided confidence bounds) when the data are normally
distributed. The basis value will
be equal to \(\bar{x} - k s\),
where \(\bar{x}\) is the sample mean,
\(s\) is the sample standard deviation and \(k\) is the result
of this function.
This function is internally used by `basis_normal()`

when
computing basis values.

k_factor_normal(n, p = 0.9, conf = 0.95)

n | the number of observations (i.e. coupons) |
---|---|

p | the desired content of the tolerance bound. Should be 0.90 for B-Basis and 0.99 for A-Basis |

conf | confidence level. Should be 0.95 for both A- and B-Basis |

the calculated factor

This function calculates the k factors used when determining A- and
B-Basis values for normally distributed data. To get \(kB\), set
the content of the tolerance bound to `p = 0.90`

and
the confidence level to `conf = 0.95`

. To get \(kA\), set
`p = 0.99`

and `conf = 0.95`

. While other tolerance bound
contents and confidence levels may be computed, they are infrequently
needed in practice.

The k-factor is calculated using equation 2.2.3 of Krishnamoorthy and Mathew (2008).

This function has been validated against the \(kB\) tables in CMH-17-1G for each value of \(n\) from \(n = 2\) to \(n = 95\). It has been validated against the \(kA\) tables in CMH-17-1G for each value of \(n\) from \(n = 2\) to \(n = 75\). Larger values of \(n\) also match the tables in CMH-17-1G, but R emits warnings that "full precision may not have been achieved." When validating the results of this function against the tables in CMH-17-1G, the maximum allowable difference between the two is 0.002. The tables in CMH-17-1G give values to three decimal places.

For more information about tolerance bounds in general, see Meeker, et. al. (2017).

K. Krishnamoorthy and T. Mathew, Statistical Tolerance Regions: Theory, Applications, and Computation. Hoboken: John Wiley & Sons, 2008.

W. Meeker, G. Hahn, and L. Escobar, Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition. Hoboken: John Wiley & Sons, 2017.

“Composite Materials Handbook, Volume 1. Polymer Matrix Composites Guideline for Characterization of Structural Materials,” SAE International, CMH-17-1G, Mar. 2012.

#> [1] 2.35464## [1] 2.35464 # This can be used to caclulate the B-Basis if # the sample mean and sample standard deviation # is known, and data is assumed to be normally # distributed sample_mean <- 90 sample_sd <- 5.2 print("B-Basis:")#> [1] "B-Basis:"#> [1] 77.75587## [1] B-Basis: ## [1] 77.75587