pbivgeo {BivGeo} | R Documentation |
Joint Cumulative Function for the Basu-Dhar Bivariate Geometric Distribution
Description
This function computes the joint cumulative function of the Basu-Dhar bivariate geometric distribution assuming arbitrary parameter values.
Usage
pbivgeo(x, y, theta, lower.tail = TRUE)
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 |
lower.tail |
logical; If TRUE (default), probabilities are |
Details
The joint cumulative function for a random vector (X
, Y
) following a Basu-Dhar bivariate geometric distribution could be written as:
P(X \le x, Y \le y) = 1 - (\theta_{1}\theta_3)^{x} - (\theta_{2}\theta_3)^{y} + \theta_{1}^{x}\theta_{2}^{y} \theta_{3}^{\max(x,y)}
and the joint survival function is given by:
P(X > x, Y > y) = \theta_{1}^{x}\theta_{2}^{y} \theta_{3}^{\max(x,y)}
Value
pbivgeo
gives the values of the cumulative function.
Invalid arguments will return an error message.
Author(s)
Ricardo P. Oliveira rpuziol.oliveira@gmail.com
Jorge Alberto Achcar achcar@fmrp.usp.br
Source
pbivgeo
is calculated directly from the definition.
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:
pbivgeo(x = 1, y = 2, theta = c(0.2, 0.4, 0.7), lower.tail = TRUE)
# [1] 0.79728
# If x is a matrix:
matr <- matrix(c(1,2,3,5), ncol = 2)
pbivgeo(x = matr, y = NULL, theta = c(0.2,0.4,0.7), lower.tail = TRUE)
# [1] 0.8424384 0.9787478
# If lower.tail = FALSE:
pbivgeo(x = 1, y = 2, theta = c(0.2, 0.4, 0.7), lower.tail = FALSE)
# [1] 0.01568
matr <- matrix(c(1,2,3,5), ncol = 2)
pbivgeo(x = matr, y = NULL, theta = c(0.9,0.4,0.7), lower.tail = FALSE)
# [1] 0.01975680 0.00139404