[R] RV: problems checking a package

Gonzalez Ruiz, Juan Ramon jrgonzalez at ico.scs.es
Tue Feb 1 16:26:10 CET 2005


 
Dear R-listers,

I have a very strange problem. I made a package (under Windows and
Linux). The package passed the R CMD Check without problem. Then, I
installed the package and executed a function which calls to a 'dll'

mod<-frailtyPenal(Surv(time,status)~sex+age+cluster(id),
+                   n.knots=8,kappa1=10000,data=kidney)

mod

Call:
frailtyPenal(formula = Surv(time, status) ~ sex + age + cluster(id), 
    data = kidney, n.knots = 8, kappa1 = 10000)


  Shared Gamma Frailty model parameter estimates
  using a Penalized Likelihood on the hazard function 

        coef exp(coef) se(coef) se(coef) HIH      z      p
sex -1.73270     0.177   0.5529       0.5026 -3.134 0.0017
age  0.00812     1.008   0.0125       0.0123  0.651 0.5200

    Frailty parameter, Theta: 0.499 (s.e.: 0.266 ) (s.e. HIH: 0.259 ) 
 
    penalized marginal log-likelihood = -325.64
    n= 76
    n events= 58 
    n groups= 38 
    number of iterations:  20



However, If we try to execute the same function once again we obtain the
following results




mod<-frailtyPenal(Surv(time,status)~sex+age+cluster(id),
+                   n.knots=8,kappa1=10000,data=kidney)

mod

Call:
frailtyPenal(formula = Surv(time, status) ~ sex + age + cluster(id), 
    data = kidney, n.knots = 8, kappa1 = 10000)


  Shared Gamma Frailty model parameter estimates
  using a Penalized Likelihood on the hazard function 

        coef exp(coef) se(coef) se(coef) HIH      z      p
sex -1.74321     0.175   0.5529       0.5026 -3.153 0.0016
age  0.00613     1.006   0.0125       0.0123  0.491 0.6200

    Frailty parameter, Theta: 14797011 (s.e.: 1449 ) (s.e. HIH: 1410 ) 
 
    penalized marginal log-likelihood = 56.63
    n= 76
    n events= 58 
    n groups= 38 
    number of iterations:  351


As you can see, parameters estimates and number of iterations are not
the same. In addition, the second execution takes about 10 seconds and
the first one only 1 or 2. Finnally, if we try to estimate the same
model once again, the PC hunks. I suspect that there is a problem with
Fortran but after proving many changes I do not find it. 

Do someone know what it is happening?


Thank you very much for any help in advance.

Best Regards,

Juan




More information about the R-help mailing list