Description Usage Arguments Value References See Also Examples
Bivariate bimodal distributions.
NOTE THAT THE ORDER OR THE FUNCTION ARGUMENTS HAS CHANGED.
(In version 0.7.x)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | bmbvpdf (
mean.X1=0, mean.X2=0,
mean.Y1=0, mean.Y2=0,
sd.X1=1, sd.X2=1,
sd.Y1=1, sd.Y2=1)
bmbvcdf (
mean.X1=0, mean.X2=0,
mean.Y1=0, mean.Y2=0,
sd.X1=1, sd.X2=1,
sd.Y1=1, sd.Y2=1)
bmbvpdf.2 (
mean.X1=0, mean.X2=0,
mean.Y1=0, mean.Y2=0,
var.X1=1, var.X2=1,
var.Y1=1, var.Y2=1)
bmbvcdf.2 (
mean.X1=0, mean.X2=0,
mean.Y1=0, mean.Y2=0,
var.X1=1, var.X2=1,
var.Y1=1, var.Y2=1)
|
mean.X1, mean.Y1 |
Numeric values, giving the means of the first X and Y components. |
sd.X1, sd.Y1 |
Positive numeric values, giving the standard deviations of the first X and Y components. |
var.X1, var.Y1 |
Positive numeric values, giving the variances of the first X and Y components. |
mean.X2, mean.Y2 |
Numeric values, giving the means of the second X and Y components. |
sd.X2, sd.Y2 |
Positive numeric values, giving the standard deviations of the second X and Y components. |
var.X2, var.Y2 |
Positive numeric values, giving the variances of the second X and Y components. |
Self-referencing S4-based function objects.
Refer to Function Objects.
Refer to the vignette for an overview, references, theoretical background and better examples.
Uniform
For uniform distributions.
Binomial, Poisson and Categorical
For other probability distributions of discrete random variables.
Normal, Dirichlet and Nonparametric
For other probability distributions of continuous random variables.
Main Plotting Functions
Density Matrices
1 2 3 4 |
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