# boot.mean

From sur v1.0.0
by Daphna Harel

##### Bootstrapped Mean

Function to obtain a sampling distribution of means by bootstrapping.

##### Usage

`boot.mean(x, B, n = length(x))`

##### Arguments

- x
original sample, given as a numeric or logical object, to be used to generate bootstrapped samples.

- B
number of bootstrapped samples to be generated by randomly sampling with replacement.

- n
size of each bootstrapped sample. Default setting is the size of the original sample.

##### Value

A list with components:

number of bootstrapped means computed.

mean of bootstrapped means.

standard error, estimated as the standard deviation of bootstrapped means.

means of bootstrapped samples.

##### See Also

##### Examples

```
# NOT RUN {
# using simple vector
a = 1:10
set.seed(1234)
boot.mean(a, B = 500)
# using variable from data frame
set.seed(1234)
boot.mean(Framingham$AGE3, B = 1000)
# }
```

*Documentation reproduced from package sur, version 1.0.0, License: GPL (>= 2)*

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