I was exploring Weibull analysis for understanding reliability of two specific specimen. I used the R package, "weibulltoolkit" and "survival" to get the plot in question. The dataset is big so I am not posting it.
X = read.table("./test", header=T) d <- data.frame(ob=X, state=1) s = Surv(d$ob, d$state) plot.wb(s)
From my understanding, both plots indicate bad fits! This could be an artifact of having too many data-points in the system or could be due to seasonal-effects or other unknown effects. Looking at the plot, what am I supposed to understand? Specifically,
- Plot 1 (using 4000 points) seems to indicate the presence of two different behaviors (0.05 - 5 and 5-1e+05). Does this mean that I am better off splitting the dataset into two and analyzing them separately? If so, what is the implication of this?
- Same seems to be going for Plot 2 (using 400 points) i.e. I would be better of splitting this dataset as well.
What is a good way of comparing these two datasets? Any suggestions?
EDIT: Upon Googling, I came across something called Multiple failure modes though I am not sure how to do this in R. Any suggestions would be greatly appreciated