dbivgeo {BivGeo} | R Documentation |
Joint Probability Mass Function for the Basu-Dhar Bivariate Geometric Distribution
Description
This function computes the joint probability mass function of the Basu-Dhar bivariate geometric distribution for arbitrary parameter values.
Usage
dbivgeo1(x, y = NULL, theta, log = FALSE)
dbivgeo2(x, y = NULL, theta, log = FALSE)
Arguments
x |
matrix or vector containing the data. If x is a matrix then it is considered as x the first column and y the second column (y argument need be setted to NULL). Additional columns and y are ignored. |
y |
vector containing the data of y. It is used only if x is also a vector. Vectors x and y should be of equal length. |
theta |
vector (of length 3) containing values of the parameters |
log |
logical argument for calculating the log probability or the probability function. The default value is FALSE. |
Details
The joint probability mass function for a random vector (X
, Y
) following a Basu-Dhar bivariate geometric distribution could be written in two forms. The first form is described by:
P(X = x, Y = y) = \theta_{1}^{x - 1} \theta_{2}^{y - 1} \theta_{3}^{z_1} - \theta_{1}^{x} \theta_{2}^{y - 1} \theta_{3}^{z_2} - \theta_{1}^{x - 1} \theta_{2}^{y} \theta_{2}^{z_3} + \theta_{1}^{x} \theta_{2}^{y} \theta_{3}^{z_4}
where x,y > 0
are positive integers and z_1 = \max(x - 1, y - 1),z_2 = \max(x, y - 1), z_3 = \max(x - 1, y), z_4 = \max(x, y)
. The second form is given by the conditions:
If X < Y, then
P(X = x, Y = y) = \theta_1^{x - 1} (\theta_2 \theta_{3})^{y - 1}(1 - \theta_{2} \theta_{3}) (1 - \theta_1)
If X = Y, then
P(X = x, Y = y) = (\theta_1 \theta_2 \theta_{3})^{x - 1}(1 - \theta_1 \theta_{3} - \theta_2 \theta_{3} + \theta_1 \theta_2 \theta_{3})
If X > Y, then
P(X = x, Y = y) = \theta_2^{y - 1} (\theta_1 \theta_{3})^{x - 1}(1 - \theta_{1} \theta_{3}) (1 - \theta_2)
Value
dbivgeo1
gives the values of the probability mass function using the first form of the joint pmf.
dbivgeo2
gives the values of the probability mass function using the second form of the joint pmf.
Invalid arguments will return an error message.
Author(s)
Ricardo P. Oliveira rpuziol.oliveira@gmail.com
Jorge Alberto Achcar achcar@fmrp.usp.br
Source
dbivgeo1
and dbivgeo2
are calculated directly from the definitions.
References
Basu, A. P., & Dhar, S. K. (1995). Bivariate geometric distribution. Journal of Applied Statistical Science, 2, 1, 33-44.
Li, J., & Dhar, S. K. (2013). Modeling with bivariate geometric distributions. Communications in Statistics-Theory and Methods, 42, 2, 252-266.
Achcar, J. A., Davarzani, N., & Souza, R. M. (2016). Basu–Dhar bivariate geometric distribution in the presence of covariates and censored data: a Bayesian approach. Journal of Applied Statistics, 43, 9, 1636-1648.
de Oliveira, R. P., & Achcar, J. A. (2018). Basu-Dhar's bivariate geometric distribution in presence of censored data and covariates: some computational aspects. Electronic Journal of Applied Statistical Analysis, 11, 1, 108-136.
See Also
Geometric
for the univariate geometric distribution.
Examples
# If x and y are integer numbers:
dbivgeo1(x = 1, y = 2, theta = c(0.2, 0.4, 0.7), log = FALSE)
# [1] 0.16128
dbivgeo2(x = 1, y = 2, theta = c(0.2, 0.4, 0.7), log = FALSE)
# [1] 0.16128
# If x is a matrix:
matr <- matrix(c(1,2,3,5), ncol = 2)
dbivgeo1(x = matr, y = NULL, theta = c(0.2,0.4,0.7), log = FALSE)
# [1] 0.0451584000 0.0007080837
dbivgeo2(x = matr, y = NULL, theta = c(0.2,0.4,0.7), log = FALSE)
# [1] 0.0451584000 0.0007080837
# If log = TRUE:
dbivgeo1(x = 1, y = 2, theta = c(0.2, 0.4, 0.7), log = TRUE)
# [1] -1.824613
dbivgeo2(x = 1, y = 2, theta = c(0.2, 0.4, 0.7), log = TRUE)
# [1] -1.824613