Type: | Package |
Title: | Visualize Probability Distributions |
Version: | 0.2.0 |
Description: | Visualize and compute percentiles/probabilities of normal, t, f, chi square and binomial distributions. |
Depends: | R(≥ 3.2) |
Imports: | ggplot2, magrittr, stats, utils |
Suggests: | covr, knitr, rmarkdown, testthat, vdiffr, xplorerr |
License: | MIT + file LICENSE |
URL: | https://github.com/rsquaredacademy/vistributions, https://vistributions.rsquaredacademy.com |
BugReports: | https://github.com/rsquaredacademy/vistributions/issues |
Encoding: | UTF-8 |
RoxygenNote: | 7.3.2 |
VignetteBuilder: | knitr |
NeedsCompilation: | no |
Packaged: | 2024-11-07 09:55:08 UTC; HP |
Author: | Aravind Hebbali [aut, cre] |
Maintainer: | Aravind Hebbali <hebbali.aravind@gmail.com> |
Repository: | CRAN |
Date/Publication: | 2024-11-07 11:10:04 UTC |
vistributions
package
Description
Visualize probability distributions.
Author(s)
Maintainer: Aravind Hebbali hebbali.aravind@gmail.com
See Also
Useful links:
Report bugs at https://github.com/rsquaredacademy/vistributions/issues
Visualize binomial distribution
Description
Visualize how changes in number of trials and the probability of success affect the shape of the binomial distribution. Compute & visualize probability from a given quantile and quantiles out of given probability.
Usage
vdist_binom_plot(n = 10, p = 0.3, print_plot = TRUE)
vdist_binom_prob(
n = 10,
p = 0.3,
s = 4,
type = c("lower", "upper", "exact", "interval"),
print_plot = TRUE
)
vdist_binom_perc(
n = 10,
p = 0.5,
tp = 0.05,
type = c("lower", "upper"),
print_plot = TRUE
)
Arguments
n |
Number of trials. |
p |
Aggregate probability. |
print_plot |
logical; if |
s |
Number of success. |
type |
Lower/upper/exact/interval. |
tp |
Probability of success in a trial. |
See Also
Examples
# visualize binomial distribution
vdist_binom_plot(10, 0.3)
# visualize probability from a given quantile
vdist_binom_prob(10, 0.3, 4, type = 'exact')
vdist_binom_prob(10, 0.3, 4, type = 'lower')
vdist_binom_prob(10, 0.3, 4, type = 'upper')
vdist_binom_prob(10, 0.3, c(4, 6), type = 'interval')
# visualize quantiles out of given probability
vdist_binom_perc(10, 0.5, 0.05)
vdist_binom_perc(10, 0.5, 0.05, "upper")
Visualize chi square distribution
Description
Visualize how changes in degrees of freedom affect the shape of the chi square distribution. Compute & visualize quantiles out of given probability and probability from a given quantile.
Usage
vdist_chisquare_plot(
df = 3,
normal = FALSE,
xaxis_range = 25,
print_plot = TRUE
)
vdist_chisquare_perc(
probs = 0.95,
df = 3,
type = c("lower", "upper"),
print_plot = TRUE
)
vdist_chisquare_prob(
perc = 13,
df = 11,
type = c("lower", "upper"),
print_plot = TRUE
)
Arguments
df |
Degrees of freedom. |
normal |
If |
xaxis_range |
The upper range of the X axis. |
print_plot |
logical; if |
probs |
Probability value. |
type |
Lower tail or upper tail. |
perc |
Quantile value. |
See Also
Examples
# visualize chi square distribution
vdist_chisquare_plot()
vdist_chisquare_plot(df = 5)
vdist_chisquare_plot(df = 5, normal = TRUE)
# visualize quantiles out of given probability
vdist_chisquare_perc(0.165, 8, 'lower')
vdist_chisquare_perc(0.22, 13, 'upper')
# visualize probability from a given quantile.
vdist_chisquare_prob(13.58, 11, 'lower')
vdist_chisquare_prob(15.72, 13, 'upper')
Visualize f distribution
Description
Visualize how changes in degrees of freedom affect the shape of the F distribution. Compute & visualize quantiles out of given probability and probability from a given quantile.
Usage
vdist_f_plot(num_df = 4, den_df = 30, normal = FALSE, print_plot = TRUE)
vdist_f_perc(
probs = 0.95,
num_df = 3,
den_df = 30,
type = c("lower", "upper"),
print_plot = TRUE
)
vdist_f_prob(
perc = 2.35,
num_df = 5,
den_df = 32,
type = c("lower", "upper"),
print_plot = TRUE
)
Arguments
num_df |
Degrees of freedom associated with the numerator of f statistic. |
den_df |
Degrees of freedom associated with the denominator of f statistic. |
normal |
If |
print_plot |
logical; if |
probs |
Probability value. |
type |
Lower tail or upper tail. |
perc |
Quantile value. |
See Also
Examples
# visualize F distribution
vdist_f_plot()
vdist_f_plot(6, 10, normal = TRUE)
# visualize probability from a given quantile
vdist_f_perc(0.95, 3, 30, 'lower')
vdist_f_perc(0.125, 9, 35, 'upper')
# visualize quantiles out of given probability
vdist_f_prob(2.35, 5, 32)
vdist_f_prob(1.5222, 9, 35, type = "upper")
Launch shiny app
Description
Launches shiny app for visualizing distributions.
Usage
vdist_launch_app()
Examples
## Not run:
vdist_launch_app ()
## End(Not run)
Visualize normal distribution
Description
Visualize how changes in mean and standard deviation affect the shape of the normal distribution. Compute & visualize quantiles out of given probability and probability from a given quantile.
Usage
vdist_normal_plot(mean = 0, sd = 1, print_plot = TRUE)
vdist_normal_perc(
probs = 0.95,
mean = 0,
sd = 1,
type = c("lower", "upper", "both"),
print_plot = TRUE
)
vdist_normal_prob(
perc = 3,
mean = 0,
sd = 1,
type = c("lower", "upper", "both"),
print_plot = TRUE
)
Arguments
mean |
Mean of the normal distribution. |
sd |
Standard deviation of the normal distribution. |
print_plot |
logical; if |
probs |
Probability value. |
type |
Lower tail, upper tail or both. |
perc |
Quantile value. |
See Also
Examples
# visualize normal distribution
vdist_normal_plot()
vdist_normal_plot(mean = 2, sd = 0.6)
# visualize quantiles out of given probability
vdist_normal_perc(0.95, mean = 2, sd = 1.36)
vdist_normal_perc(0.3, mean = 2, sd = 1.36, type = 'upper')
vdist_normal_perc(0.95, mean = 2, sd = 1.36, type = 'both')
# visualize probability from a given quantile
vdist_normal_prob(3.78, mean = 2, sd = 1.36)
vdist_normal_prob(3.43, mean = 2, sd = 1.36, type = 'upper')
vdist_normal_prob(c(-1.74, 1.83), type = 'both')
Visualize t distribution
Description
Visualize how degrees of freedom affect the shape of t distribution, visualize quantiles out of given probability and probability from a given quantile.
Usage
vdist_t_plot(df = 3, print_plot = TRUE)
vdist_t_perc(
probs = 0.95,
df = 4,
type = c("lower", "upper", "both"),
print_plot = TRUE
)
vdist_t_prob(
perc = 1.6,
df = 7,
type = c("lower", "upper", "interval", "both"),
print_plot = TRUE
)
Arguments
df |
Degrees of freedom. |
print_plot |
logical; if |
probs |
Probability value. |
type |
Lower tail, upper tail, interval or both. |
perc |
Quantile value. |
See Also
Examples
# visualize t distribution
vdist_t_plot()
vdist_t_plot(6)
vdist_t_plot(df = 8)
# visualize quantiles out of given probability
vdist_t_perc(probs = 0.95, df = 4, type = 'lower')
vdist_t_perc(probs = 0.35, df = 4, type = 'upper')
vdist_t_perc(probs = 0.69, df = 7, type = 'both')
# visualize probability from a given quantile
vdist_t_prob(2.045, 7, 'lower')
vdist_t_prob(0.945, 7, 'upper')
vdist_t_prob(1.445, 7, 'interval')
vdist_t_prob(1.6, 7, 'both')