Nothing
R/vdist-plots.R
In vistributions: Visualize Probability Distributions
Defines functions
vdist_pol_t
tprob_plot_build
tperc_plot_build
tplot_plot_build
nprob_plot_build
nperc_plot_build
vdist_pol_cord
nplot_plot_build
vdist_pol_f
fprob_plot_build
fperc_plot_build
fplot_plot_build
vdist_pol_chi
cprob_plot_build
cperc_plot_build
cplot_plot_build
bperc_plot_build
bprob_plot_build
bplot_plot_build
#' Binomial distribution plot
#'
#' Build plot for binomial distribution.
#'
#' @param data Output returned by `bplot_data_prep()`.
#' @param n Number of trials.
#' @param p Aggregate probability.
#'
#' @noRd
#'
bplot_plot_build <- function(data, n, p) {
p <-
ggplot(data$plot_data) +
geom_col(aes(x = n, y = df), fill = "blue") +
ylab("Probability") +
xlab("No. of success") +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("Mean =", data$bm, ", Std. Dev. =", data$bsd)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = seq(0, n))
return(p)
}
bprob_plot_build <- function(data, method, n, p, s) {
plot <-
ggplot(data$plot_data) +
geom_col(aes(x = n, y = df),
fill = data$cols) +
ylab("Probability") +
xlab(paste("No. of success\n", "Mean =", data$bm, ", Std. Dev. =", data$bsd)) +
scale_x_continuous(breaks = seq(0, n)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("P(X) <=", s, "=", round(data$k, 3)))
} else if (method == "upper") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("P(X) >=", s, "=", round(data$k, 3)))
} else if (method == "exact") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("P(X) =", s, "=", round(data$k, 3)))
} else {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste0("P(", s[1], " <= X <= ", s[2], ")", " = ", round(data$k, 3)))
}
return(plot)
}
bperc_plot_build <- function(data, method, n, p, tp) {
plot <-
ggplot(data$plot_data) +
geom_col(aes(x = n, y = df),
fill = data$cols) +
ylab("Probability") +
xlab("No. of success") +
scale_x_continuous(breaks = seq(0, n)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste0("P(X <= ", data$k, ") <= ", tp, ", but P(X <= ", (data$k + 1), ") > ", tp)
)
} else {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste0("P(X >= ", (data$k + 1), ") <= ", tp, ", but P(X >= ", data$k, ") > ", tp)
)
}
return(plot)
}
cplot_plot_build <- function(data, df, range, normal) {
pp <-
ggplot(data$plot_data) +
geom_line(aes(x, chi),
color = '#4682B4',
linewidth = 2) +
ggtitle(label = "Chi Square Distribution",
subtitle = paste("df =", df)) +
ylab('') +
xlab(paste("Mean =", data$chim, " Std Dev. =", data$chisd)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = seq(0, range, 2)) +
geom_polygon(data = data$poly_data,
mapping = aes(x = y, y = z),
fill = '#4682B4') +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
if (normal) {
pp <-
pp +
geom_line(data = data$nline_data,
mapping = aes(x = x, y = y),
color = '#FF4500')
}
return(pp)
}
cperc_plot_build <- function(data, method, probs, df) {
plot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = "blue") +
xlab(paste("Mean =", data$chim, " Std Dev. =", data$chisd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
plot <-
plot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
plot <-
plot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
pol_data <- vdist_pol_chi(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
plot <-
plot +
geom_polygon(data = pol_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
plot <-
plot +
geom_vline(xintercept = data$pp,
linetype = 2,
linewidth = 1) +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3) +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = seq(0, data$xm[2], by = 5))
return(plot)
}
cprob_plot_build <- function(data, method, perc, df) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = "blue") +
xlab(paste("Mean =", data$chim, " Std Dev. =", data$chisd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
pol_data <- vdist_pol_chi(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
gplot <-
gplot +
geom_polygon(data = pol_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
gplot <-
gplot +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3) +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = seq(0, data$l[data$ln], by = 5))
return(gplot)
}
vdist_pol_chi <- function(l1, l2, df) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, dchisq(seq(l1, l2, 0.01), df), 0)
data.frame(x = x, y = y)
}
fplot_plot_build <- function(data, num_df, den_df, normal) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = "blue") +
geom_polygon(data = data$poly_data,
mapping = aes(x = y, y = z),
fill = '#4682B4') +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3) +
xlab(paste("Mean =", data$fm, " Std Dev. =", data$fsd)) +
ylab('') +
ggtitle(label = 'f Distribution',
subtitle = paste("Num df =", num_df, " Den df =", den_df)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = c(-2:4)) +
scale_y_continuous(breaks = NULL)
if (normal) {
gplot <-
gplot +
geom_line(data = data$nline_data,
mapping = aes(x = x, y = y),
color = '#FF4500')
}
return(gplot)
}
fperc_plot_build <- function(data, probs, num_df, den_df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(data = data$plot_data,
mapping = aes(x = x, y = y),
color = 'blue') +
xlab(paste("Mean =", data$fm, " Std Dev. =", data$fsd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_f(data$lc[data$l1[i]], data$lc[data$l2[i]], num_df, den_df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = data$pp[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = data$pp[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = 0:5)
return(gplot)
}
fprob_plot_build <- function(data, perc, num_df, den_df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(data = data$plot_data,
mapping = aes(x = x, y = y),
color = 'blue') +
xlab(paste("Mean =", data$fm, " Std Dev. =", data$fsd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.04,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(round((1 - data$pp) * 100, 2), "%"),
x = perc + data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(round((1 - data$pp) * 100, 2), "%"),
x = perc - data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.04,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.04,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_f(data$lc[data$l1[i]], data$lc[data$l2[i]], num_df, den_df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = perc[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = perc[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = 0:max(data$l))
return(gplot)
}
vdist_pol_f <- function(l1, l2, num_df, den_df) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, df(seq(l1, l2, 0.01), num_df, den_df), 0)
data.frame(x = x, y = y)
}
nplot_plot_build <- function(data, mean, sd) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y)) +
xlab('') +
ylab('') +
ggtitle(label = "Normal Distribution",
subtitle = paste("Mean:", mean, " Standard Deviation:", sd)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_cord(data$ll[data$l1[i]], data$ll[data$l2[i]], mean, sd)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
return(gplot)
}
vdist_pol_cord <- function(l1, l2, mean, sd) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, dnorm(seq(l1, l2, 0.01), mean, sd), 0)
data.frame(x = x, y = y)
}
nperc_plot_build <- function(data, probs, mean, sd, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y)) +
xlab(paste("Mean:", mean, " Standard Deviation:", sd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3)
} else if (method == "upper") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#0000CD",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(", data$pp[1], " < X < ", data$pp[2], ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = mean,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[1] - sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[2] + sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_cord(data$lc[data$l1[i]], data$lc[data$l2[i]], mean, sd)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = data$pp[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = data$pp[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = data$l)
return(gplot)
}
nprob_plot_build <- function(data, perc, mean, sd, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y)) +
xlab(paste("Mean:", mean, " Standard Deviation:", sd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc + sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3)
} else if (method == "upper") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc - sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#0000CD",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(", perc[1], " < X < ", perc[2], ") = ", (1 - (data$pp1 + data$pp2)) * 100, "%")) +
annotate("text",
label = paste0((1 - (data$pp1 + data$pp2)) * 100, "%"),
x = mean(perc),
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp[1] * 100, "%"),
x = perc[1] - sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp[2] * 100, "%"),
x = perc[2] + sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_cord(data$lc[data$l1[i]], data$lc[data$l2[i]], mean, sd)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = perc[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = perc[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = data$l)
return(gplot)
}
tplot_plot_build <- function(data, df) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = 'blue') +
ggtitle(label = 't Distribution',
subtitle = paste("df =", df)) +
xlab('') +
ylab('') +
geom_polygon(data = data$poly_data,
mapping = aes(x = y, y = z),
fill = '#4682B4') +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = -4:4) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
return(gplot)
}
tperc_plot_build <- function(data, probs, df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = 'blue') +
xlab(paste("df =", df)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3)
} else if (method == "upper") {
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#0000CD",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(", data$pp[1], " < X < ", data$pp[2], ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = mean(data$l),
y = max(dt(data$l, df)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[1] - 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[2] + 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_t(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = data$pp[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = data$pp[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = -5:5)
return(gplot)
}
tprob_plot_build <- function(data, perc, df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = 'blue') +
xlab(paste("df =", df)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = min(data$l):max(data$l)) +
scale_y_continuous(breaks = NULL)
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_t(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
if (method == "lower") {
point_data <- data.frame(x = perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
} else if (method == "upper") {
point_data <- data.frame(x = perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
} else if (method == "interval") {
point_data <- data.frame(x1 = perc, x2 = -perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(", -perc, " < X < ", perc, ") = ", (1 - (data$pp1 + data$pp2)) * 100, "%")) +
annotate("text",
label = paste0((1 - (data$pp1 + data$pp2)) * 100, "%"),
x = 0,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp[1] * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp[2] * 100, "%"),
x = -perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_vline(xintercept = -perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x1, y = y),
shape = 4,
color = 'red',
size = 3) +
geom_point(data = point_data,
mapping = aes(x = x2, y = y),
shape = 4,
color = 'red',
size = 3)
} else {
point_data <- data.frame(x1 = perc, x2 = -perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(|X| > ", perc, ") = ", (data$pp1 + data$pp2) * 100, "%")) +
annotate("text",
label = paste0((1 - (data$pp1 + data$pp2)) * 100, "%"),
x = 0,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp[1] * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp[2] * 100, "%"),
x = -perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_vline(xintercept = -perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x1, y = y),
shape = 4,
color = 'red',
size = 3) +
geom_point(data = point_data,
mapping = aes(x = x2, y = y),
shape = 4,
color = 'red',
size = 3)
}
return(gplot)
}
vdist_pol_t <- function(l1, l2, df) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, dt(seq(l1, l2, 0.01), df), 0)
data.frame(x = x, y = y)
}
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Defines functions vdist_pol_t tprob_plot_build tperc_plot_build tplot_plot_build nprob_plot_build nperc_plot_build vdist_pol_cord nplot_plot_build vdist_pol_f fprob_plot_build fperc_plot_build fplot_plot_build vdist_pol_chi cprob_plot_build cperc_plot_build cplot_plot_build bperc_plot_build bprob_plot_build bplot_plot_build
#' Binomial distribution plot
#'
#' Build plot for binomial distribution.
#'
#' @param data Output returned by `bplot_data_prep()`.
#' @param n Number of trials.
#' @param p Aggregate probability.
#'
#' @noRd
#'
bplot_plot_build <- function(data, n, p) {
p <-
ggplot(data$plot_data) +
geom_col(aes(x = n, y = df), fill = "blue") +
ylab("Probability") +
xlab("No. of success") +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("Mean =", data$bm, ", Std. Dev. =", data$bsd)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = seq(0, n))
return(p)
}
bprob_plot_build <- function(data, method, n, p, s) {
plot <-
ggplot(data$plot_data) +
geom_col(aes(x = n, y = df),
fill = data$cols) +
ylab("Probability") +
xlab(paste("No. of success\n", "Mean =", data$bm, ", Std. Dev. =", data$bsd)) +
scale_x_continuous(breaks = seq(0, n)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("P(X) <=", s, "=", round(data$k, 3)))
} else if (method == "upper") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("P(X) >=", s, "=", round(data$k, 3)))
} else if (method == "exact") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste("P(X) =", s, "=", round(data$k, 3)))
} else {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste0("P(", s[1], " <= X <= ", s[2], ")", " = ", round(data$k, 3)))
}
return(plot)
}
bperc_plot_build <- function(data, method, n, p, tp) {
plot <-
ggplot(data$plot_data) +
geom_col(aes(x = n, y = df),
fill = data$cols) +
ylab("Probability") +
xlab("No. of success") +
scale_x_continuous(breaks = seq(0, n)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste0("P(X <= ", data$k, ") <= ", tp, ", but P(X <= ", (data$k + 1), ") > ", tp)
)
} else {
plot <-
plot +
ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
subtitle = paste0("P(X >= ", (data$k + 1), ") <= ", tp, ", but P(X >= ", data$k, ") > ", tp)
)
}
return(plot)
}
cplot_plot_build <- function(data, df, range, normal) {
pp <-
ggplot(data$plot_data) +
geom_line(aes(x, chi),
color = '#4682B4',
linewidth = 2) +
ggtitle(label = "Chi Square Distribution",
subtitle = paste("df =", df)) +
ylab('') +
xlab(paste("Mean =", data$chim, " Std Dev. =", data$chisd)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = seq(0, range, 2)) +
geom_polygon(data = data$poly_data,
mapping = aes(x = y, y = z),
fill = '#4682B4') +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
if (normal) {
pp <-
pp +
geom_line(data = data$nline_data,
mapping = aes(x = x, y = y),
color = '#FF4500')
}
return(pp)
}
cperc_plot_build <- function(data, method, probs, df) {
plot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = "blue") +
xlab(paste("Mean =", data$chim, " Std Dev. =", data$chisd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
plot <-
plot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
plot <-
plot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
pol_data <- vdist_pol_chi(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
plot <-
plot +
geom_polygon(data = pol_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
plot <-
plot +
geom_vline(xintercept = data$pp,
linetype = 2,
linewidth = 1) +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3) +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = seq(0, data$xm[2], by = 5))
return(plot)
}
cprob_plot_build <- function(data, method, perc, df) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = "blue") +
xlab(paste("Mean =", data$chim, " Std Dev. =", data$chisd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = paste("Chi Square Distribution: df =", df),
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc - data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + data$chisd,
y = max(dchisq(data$l, df)) + 0.02,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
pol_data <- vdist_pol_chi(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
gplot <-
gplot +
geom_polygon(data = pol_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
gplot <-
gplot +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3) +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = seq(0, data$l[data$ln], by = 5))
return(gplot)
}
vdist_pol_chi <- function(l1, l2, df) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, dchisq(seq(l1, l2, 0.01), df), 0)
data.frame(x = x, y = y)
}
fplot_plot_build <- function(data, num_df, den_df, normal) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = "blue") +
geom_polygon(data = data$poly_data,
mapping = aes(x = y, y = z),
fill = '#4682B4') +
geom_point(data = data$point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3) +
xlab(paste("Mean =", data$fm, " Std Dev. =", data$fsd)) +
ylab('') +
ggtitle(label = 'f Distribution',
subtitle = paste("Num df =", num_df, " Den df =", den_df)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = c(-2:4)) +
scale_y_continuous(breaks = NULL)
if (normal) {
gplot <-
gplot +
geom_line(data = data$nline_data,
mapping = aes(x = x, y = y),
color = '#FF4500')
}
return(gplot)
}
fperc_plot_build <- function(data, probs, num_df, den_df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(data = data$plot_data,
mapping = aes(x = x, y = y),
color = 'blue') +
xlab(paste("Mean =", data$fm, " Std Dev. =", data$fsd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + 0.2,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_f(data$lc[data$l1[i]], data$lc[data$l2[i]], num_df, den_df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = data$pp[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = data$pp[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = 0:5)
return(gplot)
}
fprob_plot_build <- function(data, perc, num_df, den_df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(data = data$plot_data,
mapping = aes(x = x, y = y),
color = 'blue') +
xlab(paste("Mean =", data$fm, " Std Dev. =", data$fsd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.04,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(round((1 - data$pp) * 100, 2), "%"),
x = perc + data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.02,
color = "#6495ED",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = 'f Distribution',
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(round((1 - data$pp) * 100, 2), "%"),
x = perc - data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.04,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + data$fsd,
y = max(df(data$l, num_df, den_df)) + 0.04,
color = "#0000CD",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_f(data$lc[data$l1[i]], data$lc[data$l2[i]], num_df, den_df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = perc[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = perc[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = 0:max(data$l))
return(gplot)
}
vdist_pol_f <- function(l1, l2, num_df, den_df) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, df(seq(l1, l2, 0.01), num_df, den_df), 0)
data.frame(x = x, y = y)
}
nplot_plot_build <- function(data, mean, sd) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y)) +
xlab('') +
ylab('') +
ggtitle(label = "Normal Distribution",
subtitle = paste("Mean:", mean, " Standard Deviation:", sd)) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_cord(data$ll[data$l1[i]], data$ll[data$l2[i]], mean, sd)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
return(gplot)
}
vdist_pol_cord <- function(l1, l2, mean, sd) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, dnorm(seq(l1, l2, 0.01), mean, sd), 0)
data.frame(x = x, y = y)
}
nperc_plot_build <- function(data, probs, mean, sd, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y)) +
xlab(paste("Mean:", mean, " Standard Deviation:", sd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3)
} else if (method == "upper") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#0000CD",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(", data$pp[1], " < X < ", data$pp[2], ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = mean,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[1] - sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[2] + sd,
y = max(dnorm(data$x, mean, sd)) + 0.025,
color = "#6495ED",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_cord(data$lc[data$l1[i]], data$lc[data$l2[i]], mean, sd)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = data$pp[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = data$pp[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = data$l)
return(gplot)
}
nprob_plot_build <- function(data, perc, mean, sd, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y)) +
xlab(paste("Mean:", mean, " Standard Deviation:", sd)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc + sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3)
} else if (method == "upper") {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc - sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#0000CD",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = "Normal Distribution",
subtitle = paste0("P(", perc[1], " < X < ", perc[2], ") = ", (1 - (data$pp1 + data$pp2)) * 100, "%")) +
annotate("text",
label = paste0((1 - (data$pp1 + data$pp2)) * 100, "%"),
x = mean(perc),
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp[1] * 100, "%"),
x = perc[1] - sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp[2] * 100, "%"),
x = perc[2] + sd,
y = max(dnorm(data$x, mean, sd)) + 0.07,
color = "#6495ED",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_cord(data$lc[data$l1[i]], data$lc[data$l2[i]], mean, sd)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = perc[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = perc[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = data$l)
return(gplot)
}
tplot_plot_build <- function(data, df) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = 'blue') +
ggtitle(label = 't Distribution',
subtitle = paste("df =", df)) +
xlab('') +
ylab('') +
geom_polygon(data = data$poly_data,
mapping = aes(x = y, y = z),
fill = '#4682B4') +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = -4:4) +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
return(gplot)
}
tperc_plot_build <- function(data, probs, df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = 'blue') +
xlab(paste("df =", df)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5))
if (method == "lower") {
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X < ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp - 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp + 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3)
} else if (method == "upper") {
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X > ", data$pp, ") = ", probs * 100, "%")) +
annotate("text",
label = paste0((1 - probs) * 100, "%"),
x = data$pp - 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(probs * 100, "%"),
x = data$pp + 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#0000CD",
size = 3)
} else {
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(", data$pp[1], " < X < ", data$pp[2], ") = ", probs * 100, "%")) +
annotate("text",
label = paste0(probs * 100, "%"),
x = mean(data$l),
y = max(dt(data$l, df)) + 0.025,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[1] - 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$alpha * 100, "%"),
x = data$pp[2] + 0.3,
y = max(dt(data$l, df)) + 0.025,
color = "#6495ED",
size = 3)
}
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_t(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
pln <- length(data$pp)
for (i in seq_len(pln)) {
point_data <- data.frame(x = data$pp[i], y = 0)
gplot <-
gplot +
geom_vline(xintercept = data$pp[i],
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
}
gplot <-
gplot +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = -5:5)
return(gplot)
}
tprob_plot_build <- function(data, perc, df, method) {
gplot <-
ggplot(data$plot_data) +
geom_line(aes(x = x, y = y),
color = 'blue') +
xlab(paste("df =", df)) +
ylab('') +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5)) +
scale_x_continuous(breaks = min(data$l):max(data$l)) +
scale_y_continuous(breaks = NULL)
for (i in seq_len(length(data$l1))) {
poly_data <- vdist_pol_t(data$lc[data$l1[i]], data$lc[data$l2[i]], df)
gplot <-
gplot +
geom_polygon(data = poly_data,
mapping = aes(x = x, y = y),
fill = data$col[i])
}
if (method == "lower") {
point_data <- data.frame(x = perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X < ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
} else if (method == "upper") {
point_data <- data.frame(x = perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(X > ", perc, ") = ", data$pp * 100, "%")) +
annotate("text",
label = paste0((1 - data$pp) * 100, "%"),
x = perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x, y = y),
shape = 4,
color = 'red',
size = 3)
} else if (method == "interval") {
point_data <- data.frame(x1 = perc, x2 = -perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(", -perc, " < X < ", perc, ") = ", (1 - (data$pp1 + data$pp2)) * 100, "%")) +
annotate("text",
label = paste0((1 - (data$pp1 + data$pp2)) * 100, "%"),
x = 0,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp[1] * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp[2] * 100, "%"),
x = -perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_vline(xintercept = -perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x1, y = y),
shape = 4,
color = 'red',
size = 3) +
geom_point(data = point_data,
mapping = aes(x = x2, y = y),
shape = 4,
color = 'red',
size = 3)
} else {
point_data <- data.frame(x1 = perc, x2 = -perc, y = 0)
gplot <-
gplot +
ggtitle(label = "t Distribution",
subtitle = paste0("P(|X| > ", perc, ") = ", (data$pp1 + data$pp2) * 100, "%")) +
annotate("text",
label = paste0((1 - (data$pp1 + data$pp2)) * 100, "%"),
x = 0,
y = max(dt(data$l, df)) + 0.07,
color = "#0000CD",
size = 3) +
annotate("text",
label = paste0(data$pp[1] * 100, "%"),
x = perc + 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
annotate("text",
label = paste0(data$pp[2] * 100, "%"),
x = -perc - 1,
y = max(dt(data$l, df)) + 0.07,
color = "#6495ED",
size = 3) +
geom_vline(xintercept = perc,
linetype = 2,
linewidth = 1) +
geom_vline(xintercept = -perc,
linetype = 2,
linewidth = 1) +
geom_point(data = point_data,
mapping = aes(x = x1, y = y),
shape = 4,
color = 'red',
size = 3) +
geom_point(data = point_data,
mapping = aes(x = x2, y = y),
shape = 4,
color = 'red',
size = 3)
}
return(gplot)
}
vdist_pol_t <- function(l1, l2, df) {
x <- c(l1, seq(l1, l2, 0.01), l2)
y <- c(0, dt(seq(l1, l2, 0.01), df), 0)
data.frame(x = x, y = y)
}
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