r - Generating random numbers from a truncated Gaussian -


Like most physical problems, facing the limitations of my case, I want to generate random numbers (with R) in this way as a small Gaussian distribution.

The idea is that these numbers should not depend on the value range. I have already found the package trunkrom, but this does not work: For example, here a Gaussian meaning is 0.1 and width is 0.1, but it is constrained between 0 and 1: 

 < (Vec, breaks = 100) mean (vec): code> install.packages ("truncnorm") library (truncnorm) vec = rtruncnorm (n = 100000, a = 0, b = 1, mean = 0.1, sd = 0.1) [1] 0.1289061   
 As you can see, the final means is not the given one as input, I can have the same result by using the standard rnorm function and on subseting Consequence  
 I do not want to change the wheel again, so any ideas or suggestions of more packages will be welcomed! Thanks!   
 
 
 Therefore we may have to differentiate between the original values ​​before and after the transaction, and you may be exposed In order to control sample specimens, the estimated values ​​would probably be united, although  rnorm ()  (and probably  rtruncnorm () , which I do not know) hope Is "first"; While some statisticians at stats.stackexchange.com can provide you with a more rigorous analytical solution, you may also need to customize this code based on "first" -payment (you may have to "first"), some flawless optimization - SD-parameter should also be modified):  
  myrtruncnorm & lt; - function (n, a, b, mean = 0, sd = 1) qnorm (runif (n, pnorm (a, mean) = mean, sd = sd), pnorm (b, mean = mean, sd = sd) , mean = mean, sd = sd) set.seed (1) optim (list (mean = .1, sd = 1), (x) [1]], sd = x [[2]]) - 1) ) # Returns Meaning = 0.07785390 and SD = 0.07777597, check this: x1 & lt; - myrtruncnorm (100000,0,1,0.07785390,0.07777597) hist (x1); Meaning (x1) # Does "mean = 0.1003832" stop enough?

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