k_factor_normal | R Documentation |
kB
, kA
) with normal
distributionThe 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 |
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).
the calculated factor
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.
basis_normal()
kb <- k_factor_normal(n = 10, p = 0.9, conf = 0.95)
print(kb)
## [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:")
print(sample_mean - sample_sd * kb)
## [1] B-Basis:
## [1] 77.75587
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