Displaying 2 results from an estimated 2 matches for "confidence_level".
2007 May 27
0
weibplot (Weibull plot) for R
...represented by a straight line in a so-called Weibull plot. According to my observations this is the most common way of analyzing Weibull distributed data (e.g. time to breakdown values, tensile strength values, metal fatigue).
Here comes my code:
# data 4 wbl plot
data<-c(10,25,35,90,175)
confidence_level=.95
jpeg()
library(survival)
# time to breakdown values
res<-survreg(Surv(data) ~ 1,dist='weibull')
# scale parameter:
eta=exp(res$coefficient)
# shape parameter:
beta=1/res$scale
# plot stuff
n=length(data)
plot(data,log(-log(1-ppoints(n,a=.5))),log="x",axes=FALSE,f...
2012 Sep 26
1
Change in order of names after applying "plyr" package
...12","2-Jan-12","1-Jan-12", "31-Dec-11",
"30-Dec-11"), security_rate = c(0.597,0.61,0.6,0.63,0.67,0.7,0.74,0.735, 7.61,0.795,0.796, 0.84, 8.5,8.1,8.9,8.9,8.9,9,9,9,9,9,9,9,3.21,3.22,3.12, 3.51, 3.5, 3.37, 3.25, 3, 3.07, 3, 2.94, 2.6))
param = data.frame(confidence_level = c(0.99), holding_period = c(10), calculation_method = "MC", no_simulation_mc = c(100))
library(plyr)
library(reshape2)
attach(equity_data)
attach(param)
security_names = unique(equity_data$security_id)
# (security_names are used further in R code not included here)
alpha = param...