3-function factory 3.txt - HW3 Normal distribution factory 1 Set the random seed to zero and save the random seed vector to `seed`(hint use the command

# 3-function factory 3.txt - HW3 Normal distribution factory...

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#' HW3: Normal distribution factory #' #' 1. Set the random seed to zero and save the random seed vector to `seed`. (hint: use the command `seed <- .Random.seed`). ## Do not modify this line! set.seed(0) seed<-.Random.seed #' 2. Write a function `norm_factory` that takes as input two arguments `mu` and `var` and returns a function #' that takes a number `n` as argument and returns `n` samples from a normal distribution with mean `mu` and #' variance `var`. Use `rnorm` to simulate the sampling. #' Note: you should use `force()` in `norm_factory`. ## Do not modify this line! norm_factory<-function(mu,var){ force(mu) force(var) function(n){ return(rnorm(n,mean=mu,sd=sqrt(var))) } } #' 3. Use `norm_factory` to create two functions allowing to sample from distributions with the following #' characteristics: #' - `d0_1`: from a normal distribution with mean zero and standard deviation 1 #' - `d0_2`: from a normal distribution with mean zero and standard deviation 2 #' Then, use the two functions to generate two vectors of 1000 samples from each distributions, #' and store them respectively in `s0_1` and `s0_2`.

• Fall '18
• Linxi Liu

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