> On Dec 7, 2017, at 2:51 PM, Stephanie Tsalwa <stsalwa at hotmail.com>
wrote:
>
> Assuming the days of raining during half a year of all states(provinces) of
a country is normally distributed (mean=?, standard deviation=?) with sigma (?)
equals to 2. We now have 10 data points here: 26.64, 30.65, 31.27, 33.04, 32.56,
29.10, 28.96, 26.44, 27.76, 32.27. Try to get the 95% level of CI for ?, using
parametric Bootstrap method with bootstrap size B=8000.
This has the definite appearance of a homework assignment. It also has several
other features which likewise suggest a failure to read the Posting Guide, a
link to which is at the bottom of every posting sent out from the Rhelp
mail-server.
You are advised to post credential/affiliation information and more context of
the wider goals if my assumption of HW-status is incorrect.
--
David.
(And yes I do realize that I am also not posting any affiliation information,
either, but I'm retired and am not asking for free advice, am I? Don't
follow my bad example.)>
> my code - what am i doing wrong
>
> #set sample size n, bootstrap size B
> n = 10
> b = 8000
>
>
> set a vector of days of rain into "drain"
> drain = c(26.64, 30.65, 31.27, 33.04, 32.56, 29.10, 28.96, 26.44, 27.76,
32.27)
>
> #calculate mean of the sample for days of rain
> mdr=mean(drain)
> mdr
>
> #calculate the parameter of the exponential distribution
> lambdahat = 1.0/mdr
> lambdahat
>
> #draw the bootstrap sample from Exponential
> x = rexp(n*b, lambdahat)
> x
>
> bootstrapsample = matrix(x, nrow=n, ncol=b)
> bootstrapsample
>
> # Compute the bootstrap lambdastar
> lambdastar = 1.0/colMeans(bootstrapsample)
> lambdastar
>
> # Compute the differences
> deltastar = lambdastar - lambdahat
> deltastar
>
> # Find the 0.05 and 0.95 quantile for deltastar
> d = quantile(deltastar, c(0.05,0.95))
> d
>
> # Calculate the 95% confidence interval for lambda.
> ci = lambdahat - c(d[2], d[1])
> ci
>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law