VineCopula: BiCopMetaContour – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

BiCopMetaContour

Contour Plot of Bivariate Meta Distribution

Description

Note: This function is deprecated and only available for backwards compatibility. See contour.BiCop() for contour plots of parametric copulas, and BiCopKDE() for kernel estimates.

Usage

BiCopMetaContour(
  u1 = NULL,
  u2 = NULL,
  bw = 1,
  size = 100,
  levels = c(0.01, 0.05, 0.1, 0.15, 0.2),
  family = "emp",
  par = 0,
  par2 = 0,
  PLOT = TRUE,
  margins = "norm",
  margins.par = 0,
  xylim = NA,
  obj = NULL,
  ...
)

Arguments

`u1, u2`	Data vectors of equal length with values in [0,1] (default: `u1` and `u2 = NULL`).
`bw`	Bandwidth (smoothing factor; default: `bw = 1`).
`size`	Number of grid points; default: `size = 100`.
`levels`	Vector of contour levels. For Gaussian, Student-t or exponential margins the default value (`levels = c(0.01, 0.05, 0.1, 0.15, 0.2)`) typically is a good choice. For uniform margins we recommend `levels = c(0.1, 0.3, 0.5, 0.7, 0.9, 1.1, 1.3, 1.5)` and for Gamma margins `levels = c(0.005, 0.01, 0.03, 0.05, 0.07, 0.09)`.
`family`	An integer defining the bivariate copula family or indicating an empirical contour plot: `"emp"` = empirical contour plot (default; margins can be specified by `margins`) `0` = independence copula `1` = Gaussian copula `2` = Student t copula (t-copula) `3` = Clayton copula `4` = Gumbel copula `5` = Frank copula `6` = Joe copula `7` = BB1 copula `8` = BB6 copula `9` = BB7 copula `10` = BB8 copula `13` = rotated Clayton copula (180 degrees; survival Clayton'') \cr `14` = rotated Gumbel copula (180 degrees; survival Gumbel”) `16` = rotated Joe copula (180 degrees; survival Joe'') \cr `17` = rotated BB1 copula (180 degrees; survival BB1”) `18` = rotated BB6 copula (180 degrees; survival BB6'')\cr `19` = rotated BB7 copula (180 degrees; survival BB7”) `20` = rotated BB8 copula (180 degrees; “survival BB8”) `23` = rotated Clayton copula (90 degrees) '24' = rotated Gumbel copula (90 degrees) '26' = rotated Joe copula (90 degrees) '27' = rotated BB1 copula (90 degrees) '28' = rotated BB6 copula (90 degrees) '29' = rotated BB7 copula (90 degrees) '30' = rotated BB8 copula (90 degrees) '33' = rotated Clayton copula (270 degrees) '34' = rotated Gumbel copula (270 degrees) '36' = rotated Joe copula (270 degrees) '37' = rotated BB1 copula (270 degrees) '38' = rotated BB6 copula (270 degrees) '39' = rotated BB7 copula (270 degrees) '40' = rotated BB8 copula (270 degrees) '104' = Tawn type 1 copula '114' = rotated Tawn type 1 copula (180 degrees) '124' = rotated Tawn type 1 copula (90 degrees) '134' = rotated Tawn type 1 copula (270 degrees) '204' = Tawn type 2 copula '214' = rotated Tawn type 2 copula (180 degrees) '224' = rotated Tawn type 2 copula (90 degrees) '234' = rotated Tawn type 2 copula (270 degrees)
`par`	Copula parameter; if empirical contour plot, `par = NULL` or `0` (default).
`par2`	Second copula parameter for t-, BB1, BB6, BB7, BB8, Tawn type 1 and type 2 copulas (default: `par2 = 0`).
`PLOT`	Logical; whether the results are plotted. If `PLOT = FALSE`, the values `x`, `y` and `z` are returned (see below; default: `PLOT = TRUE`).
`margins`	Character; margins for the bivariate copula contour plot. Possible margins are: `"norm"` = standard normal margins (default) `"t"` = Student t margins with degrees of freedom as specified by `margins.par` `"gamma"` = Gamma margins with shape and scale as specified by `margins.par` `"exp"` = Exponential margins with rate as specified by `margins.par` `"unif"` = uniform margins
`margins.par`	Parameter(s) of the distribution of the margins if necessary (default: `margins.par = 0`), i.e., a positive real number for the degrees of freedom of Student t margins (see `dt()`), a 2-dimensional vector of positive real numbers for the shape and scale parameters of Gamma margins (see `dgamma()`), a positive real number for the rate parameter of exponential margins (see `dexp()`).
`xylim`	A 2-dimensional vector of the x- and y-limits. By default (`xylim = NA`) standard limits for the selected margins are used.
`obj`	`BiCop` object containing the family and parameter specification.
`...`	Additional plot arguments.

Value

`x`	A vector of length `size` with the x-values of the kernel density estimator with Gaussian kernel if the empirical contour plot is chosen and a sequence of values in `xylim` if the theoretical contour plot is chosen.
`y`	A vector of length `size` with the y-values of the kernel density estimator with Gaussian kernel if the empirical contour plot is chosen and a sequence of values in `xylim` if the theoretical contour plot is chosen.
`z`	A matrix of dimension `size` with the values of the density of the meta distribution with chosen margins (see `margins` and `margins.par`) evaluated at the grid points given by `x` and `y`.

Note

The combination family = 0 (independence copula) and margins = "unif" (uniform margins) is not possible because all z-values are equal.

Author(s)

Ulf Schepsmeier, Alexander Bauer

Examples

## meta Clayton distribution  with Gaussian margins
cop <- BiCop(family = 1, tau = 0.5)
BiCopMetaContour(obj = cop, main = "Clayton - normal margins")
# better:
contour(cop, main = "Clayton - normal margins")

## empirical contour plot with standard normal margins
dat <- BiCopSim(1000, cop)
BiCopMetaContour(dat[, 1], dat[, 2], bw = 2, family = "emp",
                 main = "empirical - normal margins")
# better:
BiCopKDE(dat[, 1], dat[, 2],
        main = "empirical - normal margins")

## empirical contour plot with exponential margins
BiCopMetaContour(dat[, 1], dat[, 2], bw = 2,
                 main = "empirical - exponential margins",
                 margins = "exp", margins.par = 1)
# better:
BiCopKDE(dat[, 1], dat[, 2],
         main = "empirical - exponential margins",
         margins = "exp")

VineCopula

Statistical Inference of Vine Copulas

v2.4.1

GPL (>= 2)

Authors

Thomas Nagler [aut, cre], Ulf Schepsmeier [aut], Jakob Stoeber [aut], Eike Christian Brechmann [aut], Benedikt Graeler [aut], Tobias Erhardt [aut], Carlos Almeida [ctb], Aleksey Min [ctb, ths], Claudia Czado [ctb, ths], Mathias Hofmann [ctb], Matthias Killiches [ctb], Harry Joe [ctb], Thibault Vatter [ctb]

Initial release