UdderQuarterInfectionData (version 1.0.0)

Gamma_Frailty_Interval_Censoring: Gamma Frailty Interval Censoring

Description

Application of the Gamma Frailty Interval Censoring Model on the Udder Quarter Infection Data Set. For more information see Details.

Usage

Gamma_Frailty_Interval_Censoring(print.level = 2)

Arguments

print.level

Parameter of nlm (default=2): this argument determines the level of printing which is done during the minimization process. The default value of 0 means that no printing occurs, a value of 1 means that initial and final details are printed and a value of 2 means that full tracing information is printed.

Value

Returns a list with the NLM result in nlm and the covariance matrix in covmat.

R Code for Model

The source R code for this model can found:

• in the doc/Models_R_Code.R file in the package installation folder.

• by accessing the function by calling Gamma_Frailty_Interval_Censoring (without brackets) or getAnywhere("Gamma_Frailty_Interval_Censoring").

Details

This function fits a parametric Weibull baseline hazard frailty model with gamma distributed frailties for the udder quarter infection data taking into consideration the interval censored nature of the data. Further theoretical details can be found in the paper in the reference

References

Goethals, K., Ampe, B., Berkvens, D., Laevens, H., Janssen, P. and Duchateau, L. (2009). Modeling interval-censored, clustered cow udder quarter infection times through the shared gamma frailty model. Journal of Agricultural Biological and Environmental Statistics 14, 1-14.

Examples

# NOT RUN {
library(UdderQuarterInfectionData)
data("udderquarterinfection")

Gamma_Frailty_Interval_Censoring()
# $nlm
# $nlm$minimum
# [1] 5670.491
#
# $nlm$estimate
# [1] 3.7967246 0.1201593 1.9672298 0.8590531
#
# $nlm$gradient
# [1]  0.0002924871  0.0017653292 -0.0005460029  0.0003265086
#
# $nlm$hessian
# [,1]       [,2]      [,3]       [,4]
# [1,]   23.22965  -117.7682 -39.93813  -10.10561
# [2,] -117.76825 15471.4753 567.24283 1228.87332
# [3,]  -39.93813   567.2428 664.76359   24.63047
# [4,]  -10.10561  1228.8733  24.63047  147.76479
#
# $nlm$code
# [1] 1
#
# $nlm$iterations
# [1] 22
#
#
# $covmat
# [,1]          [,2]          [,3]         [,4]
# [1,] 0.049281911  0.0001242730  0.0027853686  0.001872592
# [2,] 0.000124273  0.0001982213 -0.0001015391 -0.001623066
# [3,] 0.002785369 -0.0001015391  0.0017306214  0.000746460
# [4,] 0.001872592 -0.0016230660  0.0007464600  0.020269244
# }