Renamed functions, added examples.

Author: VisruthSK

NAMESPACE

@@ -1,28 +1,28 @@
 # Generated by roxygen2: do not edit by hand
 
-export(addexp)
-export(addlnorm)
-export(addnorm)
-export(addt)
-export(addtnorm)
-export(binomnorm)
-export(binompower)
-export(binomprob)
-export(binomtest)
-export(boxplot)
-export(chisqrprob)
-export(dotplot)
-export(hypernorm)
-export(hyperprob)
-export(invbinom)
-export(invnorm)
-export(invt)
-export(normpower)
-export(normprob)
-export(onesamplet)
-export(summary)
-export(tprob)
-export(twosamplet)
+export(iscamaddexp)
+export(iscamaddlnorm)
+export(iscamaddnorm)
+export(iscamaddt)
+export(iscamaddtnorm)
+export(iscambinomnorm)
+export(iscambinompower)
+export(iscambinomprob)
+export(iscambinomtest)
+export(iscamboxplot)
+export(iscamchisqrprob)
+export(iscamdotplot)
+export(iscamhypernorm)
+export(iscamhyperprob)
+export(iscaminvbinom)
+export(iscaminvnorm)
+export(iscaminvt)
+export(iscamnormpower)
+export(iscamnormprob)
+export(iscamonesamplet)
+export(iscamsummary)
+export(iscamtprob)
+export(iscamtwosamplet)
 importFrom(graphics,abline)
 importFrom(graphics,axis)
 importFrom(graphics,bxp)

R/binomial.R

@@ -12,8 +12,8 @@
 #' @export
 #'
 #' @examples
-#' binomnorm(10, 20, 0.5, "two.sided")
-binomnorm <- function(k, n, prob, direction) {
+#' iscambinomnorm(k = 10, n = 20, prob = 0.5, direction = "two.sided")
+iscambinomnorm <- function(k, n, prob, direction) {
   withr::local_par(mar = c(5, 3, 1, 1))
 
   thisx <- 0:n
@@ -221,7 +221,14 @@ binomnorm <- function(k, n, prob, direction) {
 #' @export
 #'
 #' @examples
-binompower <- function(LOS, n, prob1, alternative, prob2 = NULL) {
+#' iscambinompower(LOS = 0.05, n = 20, prob1 = 0.5, alternative = "less")
+#'
+#' iscambinompower(LOS = 0.05, n = 20, prob1 = 0.5, alternative = "greater", prob2 = 0.75)
+#'
+#' iscambinompower(LOS = 0.10, n = 30, prob1 = 0.4, alternative = "two.sided")
+#'
+#' iscambinompower(LOS = 0.10, n = 30, prob1 = 0.4, alternative = "two.sided", prob2 = 0.2)
+iscambinompower <- function(LOS, n, prob1, alternative, prob2 = NULL) {
   thisx <- 0:n
   minx <- max(
     0,
@@ -423,14 +430,14 @@ binompower <- function(LOS, n, prob1, alternative, prob2 = NULL) {
 #' @export
 #'
 #' @examples
-binomprob <- function(k, n, prob, lower.tail) {
-  Description <- "iscambinomprob(k, n, prob, lower.tail) \n This function calculates tail probabilities from the binomial distribution.\r
-k is the number of successes of interest (must be integer), n and prob are the number of trials and success probability \n lower.tail is a Boolean for finding the probability above (FALSE) or below (TRUE) the inputted value (inclusive)"
-  # TODO Stop if probability is wrong
-
-  if (as.character(k) == "?") {
-    stop(Description)
+#' iscambinomprob(k = 5, n = 20, prob = 0.4, lower.tail = TRUE)
+#' iscambinomprob(k = 15, n = 30, prob = 0.3, lower.tail = FALSE)
+#' iscambinomprob(k = 22, n = 25, prob = 0.9, lower.tail = TRUE)
+iscambinomprob <- function(k, n, prob, lower.tail) {
+  if (prob < 0 || prob > 1) {
+    stop("Error: `prob` (probability) must be a numeric value between 0 and 1.")
   }
+
   withr::local_par(mar = c(4, 3, 2, 2))
   thisx <- 0:n
   minx <- max(0, n * prob - 4 * sqrt(prob * (1 - prob) * n))
@@ -499,24 +506,43 @@ k is the number of successes of interest (must be integer), n and prob are the n
 #' @param alternative "less", "greater", or "two.sided"
 #' @param conf.level Confidence level for a two-sided confidence interval.
 #'
-#' @return P-value along with a plot of the binomial distribution and/or
-#'  binomial confidence interval.
+#' @return a list of the p-value along with lower and upper bound for the calculated confidence interval.
 #' @export
 #'
 #' @examples
-binomtest <- function(
+#'
+#' iscambinomtest(
+#'   observed = 17,
+#'   n = 25,
+#'   hypothesized = 0.5,
+#'   alternative = "greater"
+#' )
+#'
+#' iscambinomtest(
+#'   observed = 12,
+#'   n = 80,
+#'   hypothesized = 0.10,
+#'   alternative = "two.sided",
+#'   conf.level = 0.95
+#' )
+#'
+#' iscambinomtest(
+#'   observed = 0.14,
+#'   n = 100,
+#'   hypothesized = 0.20,
+#'   alternative = "less"
+#' )
+#'
+#' iscambinomtest(observed = 17, n = 25, conf.level = 0.95)
+#'
+#' iscambinomtest(observed = 12, n = 80, conf.level = c(0.90, 0.95, 0.99))
+iscambinomtest <- function(
   observed,
   n,
   hypothesized = NULL,
   alternative,
   conf.level = NULL
 ) {
-  # TODO Better documentation that takes into account all parts of description
-  Description <- "iscambinomtest(observed, n, hypothesized=NULL, alternative, conf.level=NULL) \n This function performs an exact binomial test and graphs the binomial distribution and/or binomial confidence interval.\n Input the observed number of successes or sample proportion (assumed if value less than one),\n Input n = the sample size and the hypothesized probability of success  \n Optional: Input the hypothesized probability of success and form of alternative (\"less\", \"greater\", or \"two.sided\") \n Optional: Input a confidence level (one or more values) for a two-sided confidence interval.\n "
-
-  if (as.character(observed) == "?") {
-    stop(Description)
-  }
   withr::local_par(mar = c(4, 3, 2, 2))
 
   if (observed < 1) {
@@ -759,12 +785,12 @@ binomtest <- function(
 #' @export
 #'
 #' @examples
-invbinom <- function(alpha, n, prob, lower.tail) {
-  Description <- "iscaminvbinom(alpha, n, prob, lower.tail) \n This function calculates the binomial quantile of a specified probability. \n Input the desired probability and the parameters of the binomial distribution. \n Specify whether you want this is an upper tail (FALSE) or lower tail (TRUE) \n The integer that achieves at most the stated probability will be returned."
-
-  if (as.character(alpha) == "?") {
-    stop(Description)
-  }
+#' iscaminvbinom(alpha = 0.05, n = 30, prob = 0.5, lower.tail = TRUE)
+#'
+#' iscaminvbinom(alpha = 0.05, n = 30, prob = 0.5, lower.tail = FALSE)
+#'
+#' iscaminvbinom(alpha = 0.01, n = 60, prob = 0.10, lower.tail = FALSE)
+iscaminvbinom <- function(alpha, n, prob, lower.tail) {
   withr::local_par(mar = c(4, 3, 2, 2))
 
   thisx <- 0:n

R/chisqrprob.R

@@ -13,8 +13,8 @@
 #' @export
 #'
 #' @examples
-#' chisqrprob(5, 3)
-chisqrprob <- function(x_val, df) {
+#' iscamchisqrprob(5, 3)
+iscamchisqrprob <- function(x_val, df) {
   withr::local_par(mar = c(4, 4, 2, 1))
 
   minx <- 0

R/hypergeometric.R

@@ -13,8 +13,8 @@
 #' @export
 #'
 #' @examples
-#' hypernorm(1, 20, 5, 10, TRUE)
-hypernorm <- function(k, total, succ, n, lower.tail) {
+#' iscamhypernorm(1, 20, 5, 10, TRUE)
+iscamhypernorm <- function(k, total, succ, n, lower.tail) {
   # TODO rewrite so that it uses hyperprob and overlay normal?
   withr::local_par(mar = c(4, 4, 2, 1))
 
@@ -150,8 +150,8 @@ hypernorm <- function(k, total, succ, n, lower.tail) {
 #' @export
 #'
 #' @examples
-#' hyperprob(1, 20, 5, 10, TRUE)
-hyperprob <- function(k, total, succ, n, lower.tail) {
+#' iscamhyperprob(1, 20, 5, 10, TRUE)
+iscamhyperprob <- function(k, total, succ, n, lower.tail) {
   withr::local_par(mar = c(4, 4, 2, 1))
 
   if (k < 1 & k > 0) {

R/normal.R

@@ -20,7 +20,11 @@
 #' @export
 #'
 #' @examples
-normprob <- function(
+#' iscamnormprob(1.96, direction = "above")
+#' iscamnormprob(-1.5, mean = 1, sd = 2, direction = "below")
+#' iscamnormprob(0, xval2 = 1.5, direction = "between")
+#' iscamnormprob(-1, xval2 = 1, direction = "outside")
+iscamnormprob <- function(
   xval,
   mean = 0,
   sd = 1,
@@ -190,7 +194,11 @@ normprob <- function(
 #' @export
 #'
 #' @examples
-invnorm <- function(prob1, mean = 0, sd = 1, direction) {
+#' iscaminvnorm(0.05, direction = "below")
+#' iscaminvnorm(0.90, mean = 100, sd = 15, direction = "above")
+#' iscaminvnorm(0.10, direction = "outside")
+#' iscaminvnorm(0.95, direction = "between")
+iscaminvnorm <- function(prob1, mean = 0, sd = 1, direction) {
   withr::local_par(mar = c(4, 3, 2, 2))
   min <- mean - 4 * sd
   max <- mean + 4 * sd
@@ -346,7 +354,10 @@ invnorm <- function(prob1, mean = 0, sd = 1, direction) {
 #' @export
 #'
 #' @examples
-normpower <- function(LOS, n, prob1, alternative, prob2) {
+#' iscamnormpower(0.05, n = 100, prob1 = 0.5, alternative = "greater", prob2 = 0.6)
+#' iscamnormpower(0.10, n = 50, prob1 = 0.25, alternative = "less", prob2 = 0.15)
+#' iscamnormpower(0.05, n = 200, prob1 = 0.8, alternative = "two.sided", prob2 = 0.7)
+iscamnormpower <- function(LOS, n, prob1, alternative, prob2) {
   withr::local_par(mar = c(5, 4, 1, 1), mfrow = c(2, 1))
 
   minx <- max(

R/overlayDensities.R

@@ -22,9 +22,9 @@ NULL
 #' @examples
 #' set.seed(0)
 #' x <- rexp(100, rate = 0.5)
-#' addexp(x)
-#' addexp(x, main = "Your Active Title", xlab = "Exponential Data", bins = 20)
-addexp <- function(
+#' iscamaddexp(x)
+#' iscamaddexp(x, main = "Your Active Title", xlab = "Exponential Data", bins = 20)
+iscamaddexp <- function(
   x,
   main = "Histogram with exponential curve",
   xlab = deparse(substitute(x)),
@@ -54,9 +54,9 @@ addexp <- function(
 #' @examples
 #' set.seed(0)
 #' x <- rlnorm(100)
-#' addlnorm(x)
-#' addlnorm(x, main = "Your Active Title", xlab = "Log Normal Data", bins = 20)
-addlnorm <- function(
+#' iscamaddlnorm(x)
+#' iscamaddlnorm(x, main = "Your Active Title", xlab = "Log Normal Data", bins = 20)
+iscamaddlnorm <- function(
   x,
   main = "Histogram with log-normal curve",
   xlab = deparse(substitute(x)),
@@ -89,9 +89,9 @@ addlnorm <- function(
 #' @examples
 #' set.seed(0)
 #' x <- rnorm(100)
-#' addnorm(x)
-#' addnorm(x, main = "Your Active Title", xlab = "Normal Data", bins = 20)
-addnorm <- function(
+#' iscamaddnorm(x)
+#' iscamaddnorm(x, main = "Your Active Title", xlab = "Normal Data", bins = 20)
+iscamaddnorm <- function(
   x,
   main = "Histogram with normal curve",
   xlab = deparse(substitute(x)),
@@ -124,9 +124,9 @@ addnorm <- function(
 #' @examples
 #' set.seed(0)
 #' x <- rt(100, 30)
-#' addt(x, 30)
-#' addt(x, 30, main = "Your Active Title", xlab = "t Data", bins = 20)
-addt <- function(
+#' iscamaddt(x, 30)
+#' iscamaddt(x, 30, main = "Your Active Title", xlab = "t Data", bins = 20)
+iscamaddt <- function(
   x,
   df,
   main = "Histogram with t curve",
@@ -160,9 +160,9 @@ addt <- function(
 #' @examples
 #' set.seed(0)
 #' x <- rt(100, 5)
-#' addtnorm(x, 5)
-#' addtnorm(x, 5, main = "Your Active Title", xlab = "t Data", bins = 20)
-addtnorm <- function(
+#' iscamaddtnorm(x, 5)
+#' iscamaddtnorm(x, 5, main = "Your Active Title", xlab = "t Data", bins = 20)
+iscamaddtnorm <- function(
   x,
   df,
   main = "Histogram with t and normal curve",

R/plots.R

@@ -22,19 +22,19 @@ NULL
 #' @export
 #'
 #' @examples
-#' boxplot(
+#' iscamboxplot(
 #'   mtcars$mpg,
 #'   main = "mtcars Cylinders Dotplot",
 #'   xlab = "Number of Cylinders"
 #' )
-#' boxplot(
+#' iscamboxplot(
 #'   mtcars$mpg,
 #'   mtcars$am,
 #'   main = "Automatic Cars Have Better Mileage on Average",
 #'   xlab = "Mileage (miles per gallon)",
 #'   ylab = "Automatic (yes coded as 1)"
 #' )
-boxplot <- function(
+iscamboxplot <- function(
   response,
   explanatory = NULL,
   main = "",
@@ -81,19 +81,19 @@ boxplot <- function(
 #' @export
 #'
 #' @examples
-#' dotplot(
+#' iscamdotplot(
 #'   mtcars$cyl,
 #'   main = "mtcars Cylinders Dotplot",
 #'   xlab = "Number of Cylinders"
 #' )
-#' dotplot(
+#' iscamdotplot(
 #'   mtcars$mpg,
 #'   mtcars$am,
 #'   main = "Automatic Cars Have Better Mileage on Average",
 #'   xlab = "Mileage (miles per gallon)",
 #'   ylab = "Automatic (yes coded as 1)"
 #' )
-dotplot <- function(
+iscamdotplot <- function(
   response,
   explanatory = NULL,
   main = "",
@@ -131,3 +131,8 @@ dotplot <- function(
   title(main = main, xlab = xlab, ylab = ylab)
   invisible()
 }
+
+# TODO: look at lattice::histogram
+#' @noRd
+#' @keywords internal
+iscamhistogram <- function() {}

R/iscamsummary.R R/summary.RR/iscamsummary.R renamed to R/summary.R

@@ -17,9 +17,9 @@
 #' set.seed(0)
 #' fake_data <- rnorm(30) # simulating some data
 #' groups <- sample(c("group1","group2"), 30, TRUE)
-#' summary(fake_data)
-#' summary(fake_data, explanatory = groups, digits = 2) # with groups
-summary <- function(x, explanatory = NULL, digits = 3) {
+#' iscamsummary(fake_data)
+#' iscamsummary(fake_data, explanatory = groups, digits = 2) # with groups
+iscamsummary <- function(x, explanatory = NULL, digits = 3) {
   if (is.null(explanatory)) {
     output <- .getSummaryStats(x)
   } else {