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rvectorstatisticsnormal-distribution

Calling rnorm with a vector of means

When I call rnorm passing a single value as mean, it's obvious what happens: a value is generated from Normal(10,1). 

y <- rnorm(20, mean=10, sd=1)

But, I see examples of a whole vector being passed to rnorm (or rcauchy, etc..); in this case, I am not sure what the R machinery really does. For example:

a = c(10,22,33,44,5,10,30,22,100,45,97)
y <- rnorm(a, mean=a, sd=1)

Any ideas?

Solution

  • The number of random numbers rnorm generates equals the length of a. From ?rnorm:

    n: number of observations. If ‘length(n) > 1’, the length is taken to be the number required.

    To see what is happening when a is passed to the mean argument, it's easier if we change the example:

    a = c(0, 10, 100)
y = rnorm(a, mean=a, sd=1)
[1] -0.4853138  9.3630421 99.7536461

    So we generate length(a) random numbers with mean a[i].