corrTP: Correlation between two gap times

View source: R/corrTP.R

corrTPR Documentation

Correlation between two gap times


Provides the correlation between the bivariate times for some copula distributions.


corrTP(dist, corr, dist.par)



The distribution. Possible bivariate distributions are “exponential” and “weibull”.


Correlation parameter. Possible values for the bivariate exponential distribution are between -1 and 1 (0 for independency). Any value between 0 (not included) and 1 (1 for independency) is accepted for the bivariate Weibull distribution.


Vector of parameters for the allowed distributions. Two (scale) parameters for the bivariate exponential distribution and four (2 location parameters and 2 scale parameters) for the bivariate Weibull distribution. See details below.


The bivariate exponential distribution, also known as Farlie-Gumbel-Morgenstern distribution is given by


for x≥0 and y≥0. Where the marginal distribution functions F_1 and F_2 are exponential with scale parameters θ_1 and θ_2 and correlation parameter α, -1 ≤ α ≤ 1.

The bivariate Weibull distribution with two-parameter marginal distributions. It's survival function is given by


Where 0 < δ ≤ 1 and each marginal distribution has shape parameter β_i and a scale parameter θ_i, i = 1, 2.


Artur Araújo, Javier Roca-Pardiñas and Luís Meira-Machado


Araújo A, Meira-Machado L, Roca-Pardiñas J (2014). TPmsm: Estimation of the Transition Probabilities in 3-State Models. Journal of Statistical Software, 62(4), 1-29. doi: 10.18637/jss.v062.i04

Johnson N., Kotz S. (1972). Distributions in statistics: continuous multivariate distributions, John Wiley and Sons.

Lu J., Bhattacharya G. (1990). Some new constructions of bivariate weibull models. Annals of Institute of Statistical Mathematics, 42(3), 543-559. doi: 10.1007/BF00049307

See Also



# Example for the bivariate Weibull distribution
corrTP(dist = "weibull", corr = 0.5, dist.par = c(2, 7, 2, 7))

# Example for the bivariate Exponential distribution
corrTP(dist = "exponential", corr = 1, dist.par = c(1, 1))

TPmsm documentation built on Jan. 14, 2023, 1:17 a.m.