bootstrap_confidence_interval.R

bootstrap_ci <- function(data, sample_size_pct = 0.50, samples = 100, conf_level = 0.95){
    # Computes a bootstrapped confidence interval
    # INPUT: 
    #    data: a numeric vector
    #    sample_size_pct: the percentage of the input data to be used in each bootsrapped sample
    #    samples: the number of samples
    #    conf_level: the desired confidence level
    # OUTPUT:
    #    a bootstrapped conf_level confidence interval
    
    num_data_points <- length(data)
    
    sample_means <- list()
    
    for(i in 1:samples){
        sample_means[i] <- mean(sample(x = data, size = floor(num_data_points * sample_size_pct), replace = TRUE))
    }
    
    sample_means <- unlist(sample_means)
    
    ci <- sd(sample_means) * qnorm(p = conf_level+((1-conf_level)/2))
    
    return(ci)
    
}