I am attempting to plot bias of certain estimates in a simulation. The estimates are equal in all rows, but ggplot2 plots the difference as non-zero. I was expecting no blue bars in the graph below (you can ignore the other boxes):
Now if you calculate the differences between the estimated and the simulated with
df$mrdoc2_g2_hat-df$mrdoc2_g2
The output are zeroes throughout.
Am I hitting a bug in the package (unlikely) or is it a rounding problem?
df <- read.csv("df.csv")
library(ggplot2)
library(stringr)
library(dplyr)
library(tidyr)
df %>%
summarise(
mrdoc2_g1 = mean(mrdoc2_g1_hat - sqrt(g1)),
mrdoc2_g2 = mean(mrdoc2_g2_hat - sqrt(g2)),
mrdoc2_b1 = mean(mrdoc2_b1_hat - sqrt(b1)),
mrdoc2_b3 = mean(mrdoc2_b3_hat - sqrt(b3)),
mrdoc2_ra = mean(mrdoc2_ra_hat - ra),
mrdoc2_rc = mean(mrdoc2_rc_hat - rc),
mrdoc2_re = mean(mrdoc2_re_hat - re),
mrdoc2_rf = mean(mrdoc2_rf_hat - rf),
mrdoc2_ey = mean(mrdoc2_ey_hat - ey),
mrdoc2_ex = mean(mrdoc2_ex_hat - ex),
mrdoc2_ax = mean(mrdoc2_ax_hat - ax),
mrdoc2_ay = mean(mrdoc2_ay_hat - ay),
mrdoc2_cy = mean(mrdoc2_cy_hat - cy),
mrdoc2_cx = mean(mrdoc2_cx_hat - cx),
mrdoc_g1 = mean(mrdoc_g1_hat - sqrt(g1)),
mrdoc_b1 = mean(mrdoc_b1_hat - sqrt(b1)),
mrdoc_b2 = mean(mrdoc_b2_hat - sqrt(b2)),
mrdoc_ra = mean(mrdoc_ra_hat - ra),
mrdoc_rc = mean(mrdoc_rc_hat - rc),
mrdoc_ey = mean(mrdoc_ey_hat - ey),
mrdoc_ex = mean(mrdoc_ex_hat - ex),
mrdoc_ax = mean(mrdoc_ax_hat - ax),
mrdoc_ay = mean(mrdoc_ay_hat - ay),
mrdoc_cx = mean(mrdoc_cx_hat - cx),
mrdoc_cy = mean(mrdoc_cy_hat - cy),
doc_g1 = mean(doc_g1_hat - sqrt(g1)),
doc_ra = mean(doc_ra_hat - ra),
doc_rc = mean(doc_rc_hat - rc),
doc_ey = mean(doc_ey_hat - ey),
doc_ex = mean(doc_ex_hat - ex),
doc_cx = mean(doc_cx_hat - cx),
doc_cy = mean(doc_cy_hat - cy),
doc_ax = mean(doc_ax_hat - ax),
doc_ay = mean(doc_ay_hat - ay),
) %>%
# ggplot barplot colored by group x parameters
pivot_longer(c(
mrdoc2_g1,
mrdoc2_g2,mrdoc2_b3,
mrdoc2_b1,
mrdoc2_ra, mrdoc2_rc,
mrdoc2_re, mrdoc2_rf,
mrdoc2_ey, mrdoc2_ex, mrdoc2_ax, mrdoc2_ay, mrdoc2_cx, mrdoc2_cy,
mrdoc_g1,
mrdoc_b1, mrdoc_b2,
mrdoc_ra, mrdoc_rc,
mrdoc_ey, mrdoc_ex, mrdoc_ax, mrdoc_ay, mrdoc_cx, mrdoc_cy,
doc_g1,
doc_ey, doc_ex, doc_cx, doc_cy, doc_ax, doc_ay,
doc_ra, doc_rc
),
names_to="key", values_to="value") %>%
mutate(tmp = stringr::str_split_fixed(key, "_", 2),
group = tmp[,1],
key = tmp[,2]) %>%
# filter(value != 0) %>%
ggplot(aes(x=key,value, y=value, fill= group)) +
geom_bar(stat="identity", position="dodge") +
facet_wrap(~group) + # rcc scales = "free_y") +
theme(legend.position = "bottom") +
labs(x = "Parameters", y = "Diff estimated - parameter value",
title = "Only DoC parameters")
and data (sorry, it is too long for dput as it is from a simulation):
https://paste.linux.chat/?d44333cecd4f1fc2#kDKkGHRJNsTpA3WgrFSK9HtBsKPXbwYVUAUKFs4rbX2
