shadeDist: Displays Area Under Curve of Probability Density Function
In fastGraph: Fast Drawing and Shading of Graphs of Statistical Distributions

Description Usage Arguments Details Note Author(s) See Also Examples

View source: R/fastGraph.R

This function plots a probability density function, shades the area under the curve, and computes the probability.

shadeDist(xshade = NULL, ddist = "dnorm", parm1 = NULL, parm2 = NULL, lower.tail = TRUE,
          xlab=NULL, xmin = NULL, xmax = NULL, xtic = TRUE, digits.prob = 4, 
          digits.xtic = 3, is.discrete = NULL, additional.x.range = NULL, main = NULL, 
          col = c("black", "red"), lwd = 2, ...)

`xshade`	A single number or vector of two numbers, denoting values on the x-axis where shading under the curve begins and ends. However, if `NULL`, no shading occurs.
`ddist`	Character variable naming the probability density function to be graphed. May be set to "dprop" for a sample proportion, using the same arguments as `dbinom`.
`parm1`	The first argument in `ddist`, excluding the dummy argument. For example, if `ddist`="`dnorm`", then `parm1` is the `mean` from "`dnorm`". Alternatively, `parm1` may be set to be a vector of arguments, excluding the dummy argument. However, if `ddist`="dprop", then `parm1` should be set to the `size` in `dbinom`.
`parm2`	The second argument in `ddist`, excluding the dummy argument. For example, if `ddist`="`dnorm`", then `parm2` is the `sd` from "`dnorm`". Alternatively, `parm2` may be set to be a vector of arguments, excluding both the dummy argument and `parm1`. However, if `ddist`="dprop", then `parm2` should be set to the `prob` in `dbinom`.
`lower.tail`	Logical; if `TRUE` (default), the lowest region is shaded; otherwise, the next lowest region is shaded.
`xlab`	The label of the `x` variable.
`xmin`	The minimum x-value to be graphed.
`xmax`	The maximum x-value to be graphed.
`xtic`	Logical or a vector of numbers. If `xtic` is `TRUE` (default), then the numbers on the x-axis include the median and `xshade`. If `xtic` is `TRUE`, then the default numbers from `plot` are listed on the x-axis. If `xtic` is a vector of numbers, then these numbers are listed on the x-axis.
`digits.prob`	The number of significant digits listed in the probability.
`digits.xtic`	The number of significant digits listed on the x-axis.
`is.discrete`	Logical; indicating whether or not the distribution is discrete. If `is.discrete` is `NULL`, then `shadeDist` automatically makes the correct choice for density functions already named in the `stats` package.
`additional.x.range`	A vector of two additional x-values for evaluating the function. This argument would be needed only if the user is dissatisfied with the domain determined by the function. This argument is ignored if `ddist`="dprop".
`main`	The main title given for the graph.
`col`	A vector of size two, specifying the colors of the density curve and the shading, respectively.
`lwd`	The line width for discrete distributions.
`...`	Optional arguments to be passed to the `plot` function (see `par`).

When illustrating a left-sided p-value or any other left-sided probability, xshade should be a single number and set lower.tail=TRUE (default). When illustrating a right-sided p-value or any other right-sided probability, xshade should be a single number and set lower.tail=FALSE. When illustrating a two-sided p-value or any other two-sided probability, xshade should be a vector of two numbers and set lower.tail=TRUE (default). When illustrating the complement of a two-sided p-value or the complement of any other two-sided probability, xshade should be a vector of two numbers and set lower.tail=FALSE.

The numeric value of the population median typically is shown on the x-axis when xshade is not NULL, provided that this number actually fits on the x-axis; see description for argument xtic above.\ This function shadeDist calls functions getMinMax, plot, and curve.

Steven T. Garren, James Madison University, Harrisonburg, Virginia, USA

plotDist and shadePhat

par( mfrow=c(3,3) )

shadeDist( qnorm(0.975), "dnorm", 0, 1 ) # P(Z<1.96) where Z ~ N(0,1)

shadeDist( qnorm(0.975), lower.tail=FALSE ) # P(Z>1.96) where Z ~ N(0,1)

# P(40<X<60) where X~N(mu=50,sigma=10)
shadeDist( c( 40, 60 ), , 50, 10, lower.tail=FALSE, col=c("black", "lightblue") )

shadeDist( c( 40, 60 ), "dnorm", 50, 10, col=c("purple", "lightgreen") )

shadeDist( 6.8, "dchisq", 4, lower.tail=FALSE ) # Chi-squared distribution with 4 d.f.

shadeDist( c( -1.3, 1.3 ), "dt", 13 ) # t with 13 d.f.

shadeDist( 1.19, "dt", 15, 3, lower.tail=FALSE ) # t with 15 d.f. and non-centrality parameter=3

shadeDist( 2.1, "df", 4, 25, lower.tail=FALSE, col=c("hotpink","turquoise") ) # F with 4 and 25 d.f.

shadeDist( 0.6, "dprop", 20, 0.7, xmin=0.4 ) # Probability for sample proportion with n=20 and p=0.7

par( mfrow=c(1,1) )