cont.mpdf: PDF and CDF for Continuous Random Variables

In adoocavo/Rstat_M1: Basic Statistical Methods in R

PDF and CDF for Continuous Random Variables

Description

PDF and CDF for Continuous Random Variables

Usage

cont.mpdf(dist, lo, up, para, para2, ymax, mt, dcol, np = 100,
  pos1 = "topright", pos2 = "bottomright", xp1, xp2)

Arguments

dist	Name of continuous probability distribution (one of the follows) ("exp", "gamma", "weibull", "beta", "norm", "t", "chisq", "f")
lo	Lower limit of x-axis
up	Upper limit of x-axis
para	First parameter vector of PDF
para2	Second parameter vector of PDF (if necessary)
ymax	Upper limit of y-axis
mt	Graph title
dcol	Graph color vector (default as follows) c("red", "blue", "orange2", "green4", "purple", "cyan2")
np	Number of plot points, Default: 100
pos1	Legend location of PDF, Default: 'topright'
pos2	Legend location of CDF, Default: 'bottomright'
xp1	Vector of specific x values for PDF (ignore legend)
xp2	Vector of specific x values for CDF (ignore legend)

Value

None.

Examples

lamb = 1:5
cont.mpdf("exp", 0, 3, para=lamb, ymax=5)

alp = c(0.5, 1, 2, 3); rate = 1
cont.mpdf("gamma", 0, 8, para=alp, para2=rate, ymax=1.2)

th = 1; alp = c(0.5, 1, 2, 3)
cont.mpdf("weibull", 0, 5, para=alp, para2=th, ymax=1.2)

adoocavo/Rstat_M1 documentation built on March 19, 2022, 3:34 a.m.