File size: 2,712 Bytes
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library(ggthemes)
library(dplyr)
# Generate data for the normal distribution
x <- seq(-4, 4, length.out = 1000)
y <- dnorm(x)
df <- data.frame(x = x, y = y)
# Calculate quantiles
# Use ±20 for infinity
quantiles <- c(-20, qnorm(seq(0.05, 0.95, length.out = 15)), 20)
# Create data frame for the clipped vertical lines
line_data <- data.frame()
for (q in quantiles[2:(length(quantiles) - 1)]) { # Skip the ±20 points
y_at_q <- dnorm(q)
line_data <- rbind(
line_data,
data.frame(
x = q,
y_start = 0,
y_end = y_at_q
)
)
}
# Create data for filled intervals
interval_data <- data.frame()
for (i in 1:(length(quantiles) - 1)) {
x_seq <- seq(max(-4, quantiles[i]),
min(4, quantiles[i + 1]),
length.out = 100
)
interval_data <- rbind(
interval_data,
data.frame(
x = x_seq,
y = dnorm(x_seq),
group = i
)
)
}
# Create the plot
p <- ggplot() +
# Add filled intervals
geom_ribbon(
data = interval_data,
aes(x = x, ymin = 0, ymax = y, group = group),
fill = "lightgray",
alpha = 0.3
) +
# Add the normal distribution curve
geom_line(
data = df, aes(x = x, y = y),
color = "black", size = 1
) +
# Add thin dashed vertical lines for quantiles
geom_segment(
data = line_data,
aes(
x = x, xend = x,
y = y_start, yend = y_end
),
color = "black",
linetype = "dashed",
size = 0.3,
alpha = 0.7
) +
# Add quantile labels
geom_text(
data = data.frame(
x = quantiles[2:(length(quantiles) - 1)], # Skip the ±20 points
y = rep(-0.02, 15),
label = paste0("", 1:15)
),
aes(x = x, y = y, label = label),
angle = -30,
vjust = 1,
size = 4
) +
# Add infinity labels
geom_text(
data = data.frame(
x = c(-4, 4),
y = rep(-0.02, 2),
label = c("0", "16")
),
aes(x = x, y = y, label = label),
angle = -30,
vjust = 1,
size = 4
) +
# Customize the theme and labels
theme_bw(base_size = 16) +
theme(
axis.line = element_line(color = "black"),
plot.background = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major = element_blank()
) +
labs(
x = "x",
y = "Density"
) +
# Set the axis limits
scale_x_continuous(limits = c(-4, 4)) +
ylim(-0.05, 0.45) +
# Add theme customizations
theme(
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
panel.grid.minor = element_blank()
)
# Save the plot as PDF
ggsave(
"normal_quantiles.pdf",
plot = p,
width = 10, # Width in inches
height = 7, # Height in inches
device = "pdf",
dpi = 300 # High resolution
)
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