Vectorization in fitdistrplus - Project notebook for the Invasion Heterogeneity project

I need to figure out how fitdistr is vectorizing the calls to the distribution functions, so I can appropriately build the 2Dt function and think sensibly about the truncated distributions.

The gory details are below, but in summary:

The parameter values are never vectorized
x and q (passed to ddist and pdist respectively) may be vectors
x and q may have length zero (which will need to be trapped for when I’m not just passing them on to a predefined distribution) (I don’t know why!)
x and q may have values NA, NaN, Inf (again, I’ll need to do some trapping)

So I’ll make a distribution that reports its inputs:

dmylnorm <- function(x, meanlog = 0, sdlog = 1, log = FALSE) {
  cat("In dmylnorm \n")
  cat("x:", x, "\n")
  cat("meanlog:", meanlog, "\n")
  cat("sdlog:", sdlog, "\n")
  dlnorm(x, meanlog, sdlog, log)
}
dmylnorm(1:10)

In dmylnorm 
x: 1 2 3 4 5 6 7 8 9 10 
meanlog: 0 
sdlog: 1

 [1] 0.398942280 0.156874019 0.072728256 0.038153457 0.021850715
 [6] 0.013354538 0.008581626 0.005739296 0.003965747 0.002815902

dmylnorm(1, (1:10)/10)

In dmylnorm 
x: 1 
meanlog: 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 
sdlog: 1

 [1] 0.3969525 0.3910427 0.3813878 0.3682701 0.3520653 0.3332246 0.3122539
 [8] 0.2896916 0.2660852 0.2419707

pmylnorm <- function(q, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE) {
  cat("In pmylnorm \n")
  cat("q:", q, "\n")
  cat("meanlog:", meanlog, "\n")
  cat("sdlog:", sdlog, "\n")
  plnorm(q, meanlog, sdlog, lower.tail, log.p)
}

So let’s generate some data and run it through fitdist:

mydat <- rlnorm(20) 
mydat

 [1]  0.5904349  2.9247735  2.2196987  0.8539104  1.3832922  0.8819703
 [7]  2.0710698  0.1524415  2.3086514  1.2646456 16.0086215  0.8155863
[13]  0.9015805  0.2559542  1.6114184  2.1547082  0.5778989  0.6185283
[19]  0.4560678  0.6797890

fitdist(mydat, "mylnorm", start = list(meanlog = 0, sdlog = 1))

In dmylnorm 
x:  
meanlog: 0 
sdlog: 1 
In dmylnorm 
x: 0 1 Inf NaN -1 
meanlog: 0 
sdlog: 1 
In dmylnorm 
x: 0 1 NA 
meanlog: 0 
sdlog: 1 
In dmylnorm 
x: 0 1 
meanlog: 0 
sdlog: -1 
In pmylnorm 
q:  
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 0 1 Inf NaN -1 
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 0 1 NA 
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 0 1 
meanlog: 0 
sdlog: -1 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0 
sdlog: 1 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.1 
sdlog: 1 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0 
sdlog: 1.1 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.1 
sdlog: 0.9 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.075 
sdlog: 0.95 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.175 
sdlog: 0.95 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.04375 
sdlog: 0.9875 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.01875 
sdlog: 0.9375 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.0796875 
sdlog: 0.984375 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.1109375 
sdlog: 0.946875 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.06054688 
sdlog: 0.9773437 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.05585938 
sdlog: 0.9429687 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07373047 
sdlog: 0.9740234 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.05927734 
sdlog: 1.001367 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07106934 
sdlog: 0.9628418 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.08425293 
sdlog: 0.9595215 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07832642 
sdlog: 0.9639771 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07566528 
sdlog: 0.9527954 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07421417 
sdlog: 0.9687164 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.06695709 
sdlog: 0.9675812 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07548409 
sdlog: 0.9648781 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07233925 
sdlog: 0.9590034 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07374544 
sdlog: 0.9662882 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07816019 
sdlog: 0.9683245 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07284205 
sdlog: 0.9642125 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07110341 
sdlog: 0.9656226 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.06891307 
sdlog: 0.9659948 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.0720068 
sdlog: 0.9676983 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07263324 
sdlog: 0.9650839 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.0699912 
sdlog: 0.9644183 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07280688 
sdlog: 0.9658207 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07433671 
sdlog: 0.9652821 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07191173 
sdlog: 0.9655374 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07352839 
sdlog: 0.9653672 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.0723159 
sdlog: 0.9654949 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07214225 
sdlog: 0.9647581 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07264072 
sdlog: 0.9655551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07232338 
sdlog: 0.965966 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07255577 
sdlog: 0.9653044 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07464072 
sdlog: 0.9655551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07264072 
sdlog: 0.9655551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07364072 
sdlog: 0.9665551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07364072 
sdlog: 0.9645551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07264072 
sdlog: 0.9655551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07064072 
sdlog: 0.9655551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07164072 
sdlog: 0.9665551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07164072 
sdlog: 0.9645551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07364072 
sdlog: 0.9665551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07164072 
sdlog: 0.9665551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07264072 
sdlog: 0.9675551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07264072 
sdlog: 0.9655551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07364072 
sdlog: 0.9645551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07164072 
sdlog: 0.9645551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07264072 
sdlog: 0.9655551 
In dmylnorm 
x: 0.5904349 2.924773 2.219699 0.8539104 1.383292 0.8819703 2.07107 0.1524415 2.308651 1.264646 16.00862 0.8155863 0.9015805 0.2559542 1.611418 2.154708 0.5778989 0.6185283 0.4560678 0.679789 
meanlog: 0.07264072 
sdlog: 0.9635551

Fitting of the distribution ' mylnorm ' by maximum likelihood 
Parameters:
          estimate Std. Error
meanlog 0.07264072  0.2159047
sdlog   0.96555506  0.1526871

So it is using vector values of x and q, but not of the parameters. In fact, after the initial setup, it looks like it’s not using the pdist at all!

Now let’s double-check the censored data fitting:

mydatcens <- data.frame(left = floor(mydat), right = ceiling(mydat))
mydatcens

   left right
1     0     1
2     2     3
3     2     3
4     0     1
5     1     2
6     0     1
7     2     3
8     0     1
9     2     3
10    1     2
11   16    17
12    0     1
13    0     1
14    0     1
15    1     2
16    2     3
17    0     1
18    0     1
19    0     1
20    0     1

fitdistcens(mydatcens, "mylnorm", start = list(meanlog = 0, sdlog = 1))

In dmylnorm 
x:  
meanlog: 0 
sdlog: 1 
In dmylnorm 
x: 0 1 Inf NaN -1 
meanlog: 0 
sdlog: 1 
In dmylnorm 
x: 0 1 NA 
meanlog: 0 
sdlog: 1 
In dmylnorm 
x: 0 1 
meanlog: 0 
sdlog: -1 
In pmylnorm 
q:  
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 0 1 Inf NaN -1 
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 0 1 NA 
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 0 1 
meanlog: 0 
sdlog: -1 
In dmylnorm 
x:  
meanlog: 0 
sdlog: 1 
In pmylnorm 
q:  
meanlog: 0 
sdlog: 1 
In pmylnorm 
q:  
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: 0 
sdlog: 1 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: 0 
sdlog: 1 
In dmylnorm 
x:  
meanlog: 0.1 
sdlog: 1 
In pmylnorm 
q:  
meanlog: 0.1 
sdlog: 1 
In pmylnorm 
q:  
meanlog: 0.1 
sdlog: 1 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: 0.1 
sdlog: 1 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: 0.1 
sdlog: 1 
In dmylnorm 
x:  
meanlog: 0 
sdlog: 1.1 
In pmylnorm 
q:  
meanlog: 0 
sdlog: 1.1 
In pmylnorm 
q:  
meanlog: 0 
sdlog: 1.1 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: 0 
sdlog: 1.1 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: 0 
sdlog: 1.1 
In dmylnorm 
x:  
meanlog: -0.1 
sdlog: 1.1 
In pmylnorm 
q:  
meanlog: -0.1 
sdlog: 1.1 
In pmylnorm 
q:  
meanlog: -0.1 
sdlog: 1.1 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1 
sdlog: 1.1 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1 
sdlog: 1.1 
In dmylnorm 
x:  
meanlog: -0.2 
sdlog: 1.15 
In pmylnorm 
q:  
meanlog: -0.2 
sdlog: 1.15 
In pmylnorm 
q:  
meanlog: -0.2 
sdlog: 1.15 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.2 
sdlog: 1.15 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.2 
sdlog: 1.15 
In dmylnorm 
x:  
meanlog: -0.2 
sdlog: 1.25 
In pmylnorm 
q:  
meanlog: -0.2 
sdlog: 1.25 
In pmylnorm 
q:  
meanlog: -0.2 
sdlog: 1.25 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.2 
sdlog: 1.25 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.2 
sdlog: 1.25 
In dmylnorm 
x:  
meanlog: -0.3 
sdlog: 1.375 
In pmylnorm 
q:  
meanlog: -0.3 
sdlog: 1.375 
In pmylnorm 
q:  
meanlog: -0.3 
sdlog: 1.375 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.3 
sdlog: 1.375 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.3 
sdlog: 1.375 
In dmylnorm 
x:  
meanlog: -0.4 
sdlog: 1.3 
In pmylnorm 
q:  
meanlog: -0.4 
sdlog: 1.3 
In pmylnorm 
q:  
meanlog: -0.4 
sdlog: 1.3 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.4 
sdlog: 1.3 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.4 
sdlog: 1.3 
In dmylnorm 
x:  
meanlog: -0.1 
sdlog: 1.15 
In pmylnorm 
q:  
meanlog: -0.1 
sdlog: 1.15 
In pmylnorm 
q:  
meanlog: -0.1 
sdlog: 1.15 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1 
sdlog: 1.15 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1 
sdlog: 1.15 
In dmylnorm 
x:  
meanlog: -0.1 
sdlog: 1.25 
In pmylnorm 
q:  
meanlog: -0.1 
sdlog: 1.25 
In pmylnorm 
q:  
meanlog: -0.1 
sdlog: 1.25 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1 
sdlog: 1.25 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1 
sdlog: 1.25 
In dmylnorm 
x:  
meanlog: -0.125 
sdlog: 1.225 
In pmylnorm 
q:  
meanlog: -0.125 
sdlog: 1.225 
In pmylnorm 
q:  
meanlog: -0.125 
sdlog: 1.225 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.125 
sdlog: 1.225 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.125 
sdlog: 1.225 
In dmylnorm 
x:  
meanlog: -0.225 
sdlog: 1.325 
In pmylnorm 
q:  
meanlog: -0.225 
sdlog: 1.325 
In pmylnorm 
q:  
meanlog: -0.225 
sdlog: 1.325 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.225 
sdlog: 1.325 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.225 
sdlog: 1.325 
In dmylnorm 
x:  
meanlog: -0.13125 
sdlog: 1.19375 
In pmylnorm 
q:  
meanlog: -0.13125 
sdlog: 1.19375 
In pmylnorm 
q:  
meanlog: -0.13125 
sdlog: 1.19375 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.13125 
sdlog: 1.19375 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.13125 
sdlog: 1.19375 
In dmylnorm 
x:  
meanlog: -0.19375 
sdlog: 1.28125 
In pmylnorm 
q:  
meanlog: -0.19375 
sdlog: 1.28125 
In pmylnorm 
q:  
meanlog: -0.19375 
sdlog: 1.28125 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.19375 
sdlog: 1.28125 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.19375 
sdlog: 1.28125 
In dmylnorm 
x:  
meanlog: -0.146875 
sdlog: 1.215625 
In pmylnorm 
q:  
meanlog: -0.146875 
sdlog: 1.215625 
In pmylnorm 
q:  
meanlog: -0.146875 
sdlog: 1.215625 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.146875 
sdlog: 1.215625 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.146875 
sdlog: 1.215625 
In dmylnorm 
x:  
meanlog: -0.221875 
sdlog: 1.240625 
In pmylnorm 
q:  
meanlog: -0.221875 
sdlog: 1.240625 
In pmylnorm 
q:  
meanlog: -0.221875 
sdlog: 1.240625 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.221875 
sdlog: 1.240625 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.221875 
sdlog: 1.240625 
In dmylnorm 
x:  
meanlog: -0.1492188 
sdlog: 1.228906 
In pmylnorm 
q:  
meanlog: -0.1492188 
sdlog: 1.228906 
In pmylnorm 
q:  
meanlog: -0.1492188 
sdlog: 1.228906 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1492188 
sdlog: 1.228906 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1492188 
sdlog: 1.228906 
In dmylnorm 
x:  
meanlog: -0.09609375 
sdlog: 1.194531 
In pmylnorm 
q:  
meanlog: -0.09609375 
sdlog: 1.194531 
In pmylnorm 
q:  
meanlog: -0.09609375 
sdlog: 1.194531 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.09609375 
sdlog: 1.194531 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.09609375 
sdlog: 1.194531 
In dmylnorm 
x:  
meanlog: -0.1740234 
sdlog: 1.236133 
In pmylnorm 
q:  
meanlog: -0.1740234 
sdlog: 1.236133 
In pmylnorm 
q:  
meanlog: -0.1740234 
sdlog: 1.236133 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1740234 
sdlog: 1.236133 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1740234 
sdlog: 1.236133 
In dmylnorm 
x:  
meanlog: -0.1763672 
sdlog: 1.249414 
In pmylnorm 
q:  
meanlog: -0.1763672 
sdlog: 1.249414 
In pmylnorm 
q:  
meanlog: -0.1763672 
sdlog: 1.249414 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1763672 
sdlog: 1.249414 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1763672 
sdlog: 1.249414 
In dmylnorm 
x:  
meanlog: -0.154248 
sdlog: 1.224072 
In pmylnorm 
q:  
meanlog: -0.154248 
sdlog: 1.224072 
In pmylnorm 
q:  
meanlog: -0.154248 
sdlog: 1.224072 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.154248 
sdlog: 1.224072 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.154248 
sdlog: 1.224072 
In dmylnorm 
x:  
meanlog: -0.1790527 
sdlog: 1.231299 
In pmylnorm 
q:  
meanlog: -0.1790527 
sdlog: 1.231299 
In pmylnorm 
q:  
meanlog: -0.1790527 
sdlog: 1.231299 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1790527 
sdlog: 1.231299 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1790527 
sdlog: 1.231299 
In dmylnorm 
x:  
meanlog: -0.1566772 
sdlog: 1.229504 
In pmylnorm 
q:  
meanlog: -0.1566772 
sdlog: 1.229504 
In pmylnorm 
q:  
meanlog: -0.1566772 
sdlog: 1.229504 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1566772 
sdlog: 1.229504 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1566772 
sdlog: 1.229504 
In dmylnorm 
x:  
meanlog: -0.1369019 
sdlog: 1.217444 
In pmylnorm 
q:  
meanlog: -0.1369019 
sdlog: 1.217444 
In pmylnorm 
q:  
meanlog: -0.1369019 
sdlog: 1.217444 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1369019 
sdlog: 1.217444 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1369019 
sdlog: 1.217444 
In dmylnorm 
x:  
meanlog: -0.164743 
sdlog: 1.231461 
In pmylnorm 
q:  
meanlog: -0.164743 
sdlog: 1.231461 
In pmylnorm 
q:  
meanlog: -0.164743 
sdlog: 1.231461 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.164743 
sdlog: 1.231461 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.164743 
sdlog: 1.231461 
In dmylnorm 
x:  
meanlog: -0.1671722 
sdlog: 1.236893 
In pmylnorm 
q:  
meanlog: -0.1671722 
sdlog: 1.236893 
In pmylnorm 
q:  
meanlog: -0.1671722 
sdlog: 1.236893 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1671722 
sdlog: 1.236893 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1671722 
sdlog: 1.236893 
In dmylnorm 
x:  
meanlog: -0.1639412 
sdlog: 1.233688 
In pmylnorm 
q:  
meanlog: -0.1639412 
sdlog: 1.233688 
In pmylnorm 
q:  
meanlog: -0.1639412 
sdlog: 1.233688 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1639412 
sdlog: 1.233688 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1639412 
sdlog: 1.233688 
In dmylnorm 
x:  
meanlog: -0.172007 
sdlog: 1.235644 
In pmylnorm 
q:  
meanlog: -0.172007 
sdlog: 1.235644 
In pmylnorm 
q:  
meanlog: -0.172007 
sdlog: 1.235644 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.172007 
sdlog: 1.235644 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.172007 
sdlog: 1.235644 
In dmylnorm 
x:  
meanlog: -0.1605097 
sdlog: 1.231039 
In pmylnorm 
q:  
meanlog: -0.1605097 
sdlog: 1.231039 
In pmylnorm 
q:  
meanlog: -0.1605097 
sdlog: 1.231039 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1605097 
sdlog: 1.231039 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1605097 
sdlog: 1.231039 
In dmylnorm 
x:  
meanlog: -0.1613115 
sdlog: 1.228812 
In pmylnorm 
q:  
meanlog: -0.1613115 
sdlog: 1.228812 
In pmylnorm 
q:  
meanlog: -0.1613115 
sdlog: 1.228812 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1613115 
sdlog: 1.228812 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1613115 
sdlog: 1.228812 
In dmylnorm 
x:  
meanlog: -0.1619689 
sdlog: 1.230031 
In pmylnorm 
q:  
meanlog: -0.1619689 
sdlog: 1.230031 
In pmylnorm 
q:  
meanlog: -0.1619689 
sdlog: 1.230031 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1619689 
sdlog: 1.230031 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1619689 
sdlog: 1.230031 
In dmylnorm 
x:  
meanlog: -0.1577356 
sdlog: 1.22961 
In pmylnorm 
q:  
meanlog: -0.1577356 
sdlog: 1.22961 
In pmylnorm 
q:  
meanlog: -0.1577356 
sdlog: 1.22961 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1577356 
sdlog: 1.22961 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1577356 
sdlog: 1.22961 
In dmylnorm 
x:  
meanlog: -0.1629912 
sdlog: 1.230998 
In pmylnorm 
q:  
meanlog: -0.1629912 
sdlog: 1.230998 
In pmylnorm 
q:  
meanlog: -0.1629912 
sdlog: 1.230998 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1629912 
sdlog: 1.230998 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1629912 
sdlog: 1.230998 
In dmylnorm 
x:  
meanlog: -0.1644504 
sdlog: 1.22999 
In pmylnorm 
q:  
meanlog: -0.1644504 
sdlog: 1.22999 
In pmylnorm 
q:  
meanlog: -0.1644504 
sdlog: 1.22999 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1644504 
sdlog: 1.22999 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1644504 
sdlog: 1.22999 
In dmylnorm 
x:  
meanlog: -0.1614949 
sdlog: 1.230777 
In pmylnorm 
q:  
meanlog: -0.1614949 
sdlog: 1.230777 
In pmylnorm 
q:  
meanlog: -0.1614949 
sdlog: 1.230777 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1614949 
sdlog: 1.230777 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1614949 
sdlog: 1.230777 
In dmylnorm 
x:  
meanlog: -0.1625171 
sdlog: 1.231744 
In pmylnorm 
q:  
meanlog: -0.1625171 
sdlog: 1.231744 
In pmylnorm 
q:  
meanlog: -0.1625171 
sdlog: 1.231744 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1625171 
sdlog: 1.231744 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1625171 
sdlog: 1.231744 
In dmylnorm 
x:  
meanlog: -0.1623801 
sdlog: 1.231316 
In pmylnorm 
q:  
meanlog: -0.1623801 
sdlog: 1.231316 
In pmylnorm 
q:  
meanlog: -0.1623801 
sdlog: 1.231316 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1623801 
sdlog: 1.231316 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1623801 
sdlog: 1.231316 
In dmylnorm 
x:  
meanlog: -0.1608838 
sdlog: 1.231094 
In pmylnorm 
q:  
meanlog: -0.1608838 
sdlog: 1.231094 
In pmylnorm 
q:  
meanlog: -0.1608838 
sdlog: 1.231094 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1608838 
sdlog: 1.231094 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1608838 
sdlog: 1.231094 
In dmylnorm 
x:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1624643 
sdlog: 1.231022 
In dmylnorm 
x:  
meanlog: -0.1633495 
sdlog: 1.231561 
In pmylnorm 
q:  
meanlog: -0.1633495 
sdlog: 1.231561 
In pmylnorm 
q:  
meanlog: -0.1633495 
sdlog: 1.231561 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1633495 
sdlog: 1.231561 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1633495 
sdlog: 1.231561 
In dmylnorm 
x:  
meanlog: -0.1619585 
sdlog: 1.230973 
In pmylnorm 
q:  
meanlog: -0.1619585 
sdlog: 1.230973 
In pmylnorm 
q:  
meanlog: -0.1619585 
sdlog: 1.230973 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1619585 
sdlog: 1.230973 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1619585 
sdlog: 1.230973 
In dmylnorm 
x:  
meanlog: -0.1604643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1604643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1604643 
sdlog: 1.231022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1604643 
sdlog: 1.231022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1604643 
sdlog: 1.231022 
In dmylnorm 
x:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1624643 
sdlog: 1.231022 
In dmylnorm 
x:  
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1614643 
sdlog: 1.232022 
In dmylnorm 
x:  
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1614643 
sdlog: 1.230022 
In dmylnorm 
x:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1624643 
sdlog: 1.231022 
In dmylnorm 
x:  
meanlog: -0.1644643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1644643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1644643 
sdlog: 1.231022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1644643 
sdlog: 1.231022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1644643 
sdlog: 1.231022 
In dmylnorm 
x:  
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1634643 
sdlog: 1.232022 
In dmylnorm 
x:  
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1634643 
sdlog: 1.230022 
In dmylnorm 
x:  
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1614643 
sdlog: 1.232022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1614643 
sdlog: 1.232022 
In dmylnorm 
x:  
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1634643 
sdlog: 1.232022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1634643 
sdlog: 1.232022 
In dmylnorm 
x:  
meanlog: -0.1624643 
sdlog: 1.233022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.233022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.233022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1624643 
sdlog: 1.233022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1624643 
sdlog: 1.233022 
In dmylnorm 
x:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1624643 
sdlog: 1.231022 
In dmylnorm 
x:  
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1614643 
sdlog: 1.230022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1614643 
sdlog: 1.230022 
In dmylnorm 
x:  
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q:  
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1634643 
sdlog: 1.230022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1634643 
sdlog: 1.230022 
In dmylnorm 
x:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1624643 
sdlog: 1.231022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1624643 
sdlog: 1.231022 
In dmylnorm 
x:  
meanlog: -0.1624643 
sdlog: 1.229022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.229022 
In pmylnorm 
q:  
meanlog: -0.1624643 
sdlog: 1.229022 
In pmylnorm 
q: 1 3 3 1 2 1 3 1 3 2 17 1 1 1 2 3 1 1 1 1 
meanlog: -0.1624643 
sdlog: 1.229022 
In pmylnorm 
q: 0 2 2 0 1 0 2 0 2 1 16 0 0 0 1 2 0 0 0 0 
meanlog: -0.1624643 
sdlog: 1.229022

Fitting of the distribution ' mylnorm ' on censored data by maximum likelihood 
Parameters:
          estimate
meanlog -0.1624643
sdlog    1.2310220