trapezoid | R Documentation |
Density function, distribution function, quantile function, and random generation for the trapezoidal distribution with minimum equal to min, lower mode equal to mode1, upper mode equal to mode2, and maximum equal to max. For the generalized trapezoidal distribution, n1, n3, and alpha may optionally be specified.
dtrapezoid(x, min = 0, mode1 = 1/3, mode2 = 2/3, max = 1, n1 = 2, n3 = 2, alpha = 1, log = FALSE) ptrapezoid(q, min = 0, mode1 = 1/3, mode2 = 2/3, max = 1, n1 = 2, n3 = 2, alpha = 1, lower.tail = TRUE, log.p = FALSE) qtrapezoid(p, min = 0, mode1 = 1/3, mode2 = 2/3, max = 1, n1 = 2, n3 = 2, alpha = 1, lower.tail = TRUE, log.p = FALSE) rtrapezoid(n, min = 0, mode1 = 1/3, mode2 = 2/3, max = 1, n1 = 2, n3 = 2, alpha = 1)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If length(n) > 1, the length is taken to be the number required. |
min |
vector of minima. |
mode1 |
vector of lower modes. |
mode2 |
vector of upper modes. |
max |
vector of maxima. |
n1 |
vector of growth parameters. |
n3 |
vector of decay parameters. |
alpha |
vector of boundary ratio parameters. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
The generalized trapezoidal distribution is described by van Dorp and Kotz (2003) and van Dorp and colleagues (2007). With n1, n3, and alpha equal to the default values of 2, 2, and 1, respectively, the distribution shape is of a quadrilateral trapezoid. Altering n1, n3, or alpha changes the growth rate, decay rate, and boundary ratio parameters, respectively, as demonstrated in the examples below.
dtrapezoid gives the density function, ptrapezoid gives the distribution function, qtrapezoid gives the quantile function, and rtrapezoid generates random deviates.
Jeremy Thoms Hetzel jthetzel@gmail.com
van Dorp, J. R. and Kotz, S. (2003) Generalized trapezoidal distributions. Metrika. 58(1):85–97. Preprint available: http://www.seas.gwu.edu/~dorpjr/Publications/JournalPapers/Metrika2003VanDorp.pdf
van Dorp, J. R., Rambaud, S.C., Perez, J. G., and Pleguezuelo, R. H. (2007) An elicitation procedure for the generalized trapezoidal distribution with a uniform central stage. Decision Analysis Journal. 4:156–166. Preprint available: http://www.seas.gwu.edu/~dorpjr/Publications/JournalPapers/DA2007.pdf
Distributions for standard distributions.
## Plot default trapezoid distribution curve(dtrapezoid(x, min = 0, mode1 = 1/3, mode2 = 2/3, max = 1, n1 = 2, n3 = 2, alpha = 1), from = 0, to = 1) ## Plot triangular trapezoid distribution curve(dtrapezoid(x, min = 0, mode1 = 1/2, mode2 = 1/2, max = 1, n1 = 2, n3 = 2, alpha = 1), from = 0, to = 1) ## Explore effects of n1, n3, and alpha parameters # plyr and ggplot2 are required for this example require(plyr) require(ggplot2) x <- seq(from = 0, to = 1, by = 0.01) # Create a list of arguments, varying n1, n3, and alpha arguments <- list() arguments[['A']] <- list(x = x, n1 = 2, n3 = 2, alpha = 0.8) arguments[['B']] <- list(x = x, n1 = 1.5, n3 = 1.5, alpha = 1) arguments[['C']] <- list(x = x, n1 = 2.5, n3 = 2.5, alpha = 1.5) arguments[['D']] <- list(x = x, n1 = 1.5, n3 = 2.5, alpha = 0.5) arguments[['E']] <- list(x = x, n1 = 2.5, n3 = 1.5, alpha = 1) arguments[['F']] <- list(x = x, n1 = 0.5, n3 = 0.5, alpha = 1.5) arguments[['G']] <- list(x = x, n1 = 1.5, n3 = 0.5, alpha = 0.5) arguments[['H']] <- list(x = x, n1 = 2.5, n3 = 0.5, alpha = 1) arguments[['I']] <- list(x = x, n1 = 0.5, n3 = 1.5, alpha = 1.5) arguments[['J']] <- list(x = x, n1 = 0.5, n3 = 2.5, alpha = 0.5) # Calculate the distributions plot.data <- ldply(arguments, function(z) { x <- z$x density <- dtrapezoid(x = z$x, min = 0, mode1 = 0.2, mode2 = 0.8, max = 1, n1 = z$n1, n3 = z$n3, alpha = z$alpha) args <- paste("n1 = ", z$n1, ", n3 = ", z$n3, ", alpha = ", z$alpha, sep="", collapse="") out <- data.frame(x, density, args) }) # Create labels for later use in displaying the arguments on the plots plot.data$label <- paste(plot.data$.id, ": ", plot.data$args, sep="") # Create plots generalizedTrapezoids <- ggplot(data = plot.data, aes(x = x, y = density)) + geom_line() + theme_bw() + facet_wrap(~label, ncol = 2, scales = "free_y") print(generalizedTrapezoids)
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