File size: 1,556 Bytes
998922f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | # Load required library
library(ggplot2)
# Create a function for each distribution type
mesokurtic <- function(x) {
dnorm(x, mean = 0, sd = 1)
}
leptokurtic <- function(x) {
dnorm(x, mean = 0, sd = 0.8) * 1.3 # Reduced scaling factor
}
platykurtic <- function(x) {
dnorm(x, mean = 0, sd = 1.6) * 0.85
}
# Create sequence of x values
x <- seq(-4, 4, length.out = 200)
# Create data frame for plotting
plot_data <- data.frame(
x = rep(x, 3),
y = c(
leptokurtic(x),
mesokurtic(x),
platykurtic(x)
),
Distribution = factor(
rep(
c(
"Leptokurtic",
"Mesokurtic",
"Platykurtic"
),
each = length(x)
),
levels = c(
"Leptokurtic",
"Mesokurtic",
"Platykurtic"
)
)
)
# Create the plot
plt <- ggplot() +
# Add the distribution curves
geom_line(
data = plot_data,
aes(x = x, y = y, color = Distribution),
size = 1
) +
# Customize colors
scale_color_manual(values = c(
"Leptokurtic" = "#007bff",
"Mesokurtic" = "#28a745",
"Platykurtic" = "#e83e8c"
)) +
# Customize labels and theme
labs(
x = "X",
y = "Probability density",
color = NULL
) +
theme_minimal() +
theme(
axis.title.y = element_text(angle = 90),
legend.position = "bottom",
legend.text = element_text(size = 12),
) +
# Set appropriate plot boundaries with higher y-limit
coord_cartesian(xlim = c(-3.5, 3.5), ylim = c(0, 0.65))
ggsave(
"pdfs/kurtosis.pdf",
plot = plt,
create.dir = TRUE,
height = 4,
width = 5
)
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