R/dist-stdSlider.R

In fGarch: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library General Public License for more details.
#
# You should have received a copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA  02111-1307  USA


################################################################################
# FUNCTION:             DESCRIPTION:
#  stdSlider             Displays Variance-1 Student-t Distribution and RVS
################################################################################


stdSlider <-
function(type = c("dist", "rand"))
{
    # A function implemented by Diethelm Wuertz

    # Description:
    #   Displays interactively Student-t distribution

    # Note:
    #   dstd(x, mean = 0, sd = 1, nu = 5)


    # FUNCTION:

    # Internal Function:
    refresh.code = function(...)
    {
        # Sliders:
        N      = .sliderMenu(no = 1)
        mean   = .sliderMenu(no = 2)
        sd     = .sliderMenu(no = 3)
        nu     = .sliderMenu(no = 4)

        # Compute Data:
        xmin = round(qstd(0.01, mean, sd, nu), digits = 2)
        xmax = round(qstd(0.99, mean, sd, nu), digits = 2)
        s = seq(xmin, xmax, length = N)
        y1 = dstd(s, mean, sd, nu)
        y2 = pstd(s, mean, sd, nu)
        main1 = paste("Student-t Density\n",
            "mean = ", as.character(mean), " | ",
            "sd = ", as.character(sd), " | ",
            "nu = ", as.character(nu))
        main2 = paste("Student-t Probability\n",
            "xmin [0.01] = ", as.character(xmin), " | ",
            "xmax [0.99] = ", as.character(xmax) )

        # Random Numbers:
        if (type[1] == "rand") {
            x = rstd(N, mean, sd, nu)
        }

        # Frame:
        par(mfrow = c(2, 1), cex = 0.7)

        # Density:
        if (type[1] == "rand") {
            hist(x, probability = TRUE, col = "steelblue", border = "white",
                breaks = "FD",
                xlim = c(xmin, xmax), ylim = c(0, 1.1*max(y1)), main = main1 )
            lines(s, y1, col = "orange")
        } else {
            plot(s, y1, type = "l", xlim = c(xmin, xmax), col = "steelblue")
            abline (h = 0, lty = 3)
            title(main = main1)
            grid()
        }

        # Probability:
        plot(s, y2, type = "l", xlim = c(xmin, xmax), ylim = c(0, 1),
            col = "steelblue" )
        abline (h = 0, lty = 3)
        title(main = main2)
        grid()

        # Frame:
        par(mfrow = c(1, 1), cex = 0.7)
    }

    # Open Slider Menu:
    .sliderMenu(refresh.code,
       names =       c(   "N", "mean",  "sd",  "nu"),
       minima =      c(   10,   -5.0,    0.1,   2.1),
       maxima =      c(  500,   +5.0,    5.0,  10.0),
       resolutions = c(   10,    0.1,    0.1,   0.1),
       starts =      c(  100,    0.0,    1.0,   5.0)
    )
}


################################################################################