Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
message = FALSE,
warning = FALSE,
fig.width = 8,
fig.height = 4.5,
fig.align = 'center',
out.width='95%',
dpi = 100,
collapse = TRUE,
comment = "#>"
)
## ----setup, message=FALSE, warning=FALSE--------------------------------------
library(healthyR.ts)
library(ggplot2)
library(dplyr)
## ----ts_random_walk-----------------------------------------------------------
df <- ts_random_walk()
head(df)
glimpse(df)
## ----ts_random_walk_ggplot_layers---------------------------------------------
df %>%
ggplot(
mapping = aes(
x = x
, y = cum_y
, color = factor(run)
, group = factor(run)
)
) +
geom_line(alpha = 0.8) +
ts_random_walk_ggplot_layers(df)
## -----------------------------------------------------------------------------
library(dplyr)
library(ggplot2)
df %>%
group_by(x) %>%
summarise(
min_y = min(cum_y),
max_y = max(cum_y)
) %>%
ggplot(
aes(x = x)
) +
geom_line(aes(y = max_y), color = "steelblue") +
geom_line(aes(y = min_y), color = "firebrick") +
geom_ribbon(aes(ymin = min_y, ymax = max_y), alpha = 0.2) +
ts_random_walk_ggplot_layers(df)
## -----------------------------------------------------------------------------
# Random Walk for volatility range 1-15%
df1 <- ts_random_walk(.sd = 0.01)
df2 <- ts_random_walk(.sd = 0.05)
df3 <- ts_random_walk(.sd = 0.10)
df4 <- ts_random_walk(.sd = 0.15)
# Merge data frames into one
df_merged <- dplyr::bind_rows(
df1 %>% mutate(ver = "A) Vol 1%"),
df2 %>% mutate(ver = "B) Vol 5%"),
df3 %>% mutate(ver = "C) Vol 10%"),
df4 %>% mutate(ver = "D) Vol 15%")
)
# Plot range between minimum and maximum values
df_merged %>%
ggplot(aes(
x = x, y = cum_y,
color = factor(run), group = factor(run)
)) +
geom_line(alpha = 0.8) +
labs(title = "", x = "", y = "") +
facet_wrap(~ver, scales = "free") +
scale_y_continuous(labels = scales::comma) +
theme(legend.position = "none")
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