addt.predint.ybar.mle: Prediction of the mean of future observations

In ADDT: Analysis of Accelerated Destructive Degradation Test Data

Description

Given observations for one temperature level up to some time point, computes a prediction interval for the mean degradation level at some future time point.

Usage

addt.predint.ybar.mle(obj, conflevel, num.fut.obs = 5, temp, tt)

Arguments

obj	An addt.fit object.
conflevel	The confidence level of the prediction interval. This argument is in decimal form (i.e., 95% is 0.95).
num.fut.obs	The number of future observations within a batch at the future time point.
temp	The temperature level at which predictions are to be made.
tt	The future time point where prediction is desired.

Value

Returns a vector containing the lower and upper bounds of the prediction interval.

Note

This function only works with an object resulted from ML approach.

References

Y. Hong, C. B. King, Y. Xie, J. H. Van Mullekom, S. P. Dehart, and P. A. DeFeo (2014). “A Comparison of Least Squares and Maximum Likelihood Approaches to Estimating Thermal Indices for Polymeric Materials,” Journal of Quality Technology, in press, 2016.

See Also

addt.fit

ADDT documentation built on May 2, 2019, 6:38 a.m.