Estimate the sample mean

Estimate the sample mean

estimate_mean(x, y, ...)

# S3 method for default
estimate_mean(x, y, ...)

# S3 method for formula
estimate_mean(x, y, data, ...)

Arguments

x

a vector of values or a formula
y

optional, a grouping vector
...

additional arguments passed to child functions
data

optional location to find formula values

Value

a posterior distribution for the mean

Methods (by class)

  • default: Default method

  • formula: Method for a formula

See also

inzposterior

Examples

post <- estimate_mean(rnorm(100, 50, 5))
summary(post)
#> 
#> Iterations = 1001:2000
#> Thinning interval = 1 
#> Number of chains = 1 
#> Sample size per chain = 1000 
#> 
#> 1. Empirical mean and standard deviation for each variable,
#>    plus standard error of the mean:
#> 
#>         Mean     SD Naive SE Time-series SE
#> mu     50.00 0.4551  0.01439        0.01347
#> sigma2 21.03 2.9734  0.09403        0.08882
#> 
#> 2. Quantiles for each variable:
#> 
#>         2.5%   25%   50%   75% 97.5%
#> mu     49.05 49.71 49.99 50.31 50.88
#> sigma2 15.99 18.99 20.78 22.80 27.56
#> 
plot(post)