20201019 Notes

Andrei R. Akhmetzhanov

2020-10-19

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First, loading necessary libraries:

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(magrittr)
library(ggplot2)

Suppose I have the following data frame:

df = data.frame(n = 5:24, q2.5 = rnorm(20, 1, 0.1), median = rnorm(20, 4, .2), q97.5 = rnorm(20, 6, .05))

where the first column is the size parameters, median, q2.5, q97.5 are the median, 2.5th and 97.5th quantiles derived from each sample. The latter is the set of recorded means/medians for each particular case.

Then we may create the following plot:

df %>%
    ggplot(aes(x=n)) +
      geom_line(aes(y=median), size=1.25, color='black') +
      geom_line(aes(y=q2.5), size=.5, color='black', linetype='dashed') +
      geom_line(aes(y=q97.5), size=.5, color='black', linetype='dashed') +
      coord_cartesian(ylim=c(0,8)) +
      xlab('n') + ylab('mean') +
      theme_classic()