bootdht parallel random number generation seed and replication

[dill]

As raised by @lenthomas in #44, it would be nice to set the RNG when running the bootstrap in parallel. See doRNG.

[dill]

doRNG added as a suggested package to deal with this issue.

library(Distance)
data("minke")
easy <- ds(data=minke, key="hr", truncation=1.5)
ex.N <- function(ests, fit) {
  return(data.frame(Label = ests$individuals$N$Label,
                    Dhat = ests$individuals$N$Estimate))
}

easyboot <- bootdht(model=easy, flatfile=minke, nboot=10, cores = 3,
                    summary_fun = ex.N)
easyboot2 <- bootdht(model=easy, flatfile=minke, nboot=10, cores = 3,
                    summary_fun = ex.N)

Yields:

> cbind(easyboot, easyboot2)
   Label      Dhat bootstrap_ID Label       Dhat bootstrap_ID
1  North 19083.401            1 North  35283.497            1
2  South  5119.951            1 South   6600.605            1
3  Total 24203.352            1 Total  41884.101            1
4  North 16208.894            2 North  24095.007            2
5  South  3509.791            2 South   5379.405            2
6  Total 19718.685            2 Total  29474.412            2
7  North 24356.201            3 North 425064.211            3
8  South  4777.667            3 South 267960.427            3
9  Total 29133.869            3 Total 693024.639            3
10 North 20646.008            4 North  37885.080            4
11 South  4584.703            4 South  11117.031            4
12 Total 25230.711            4 Total  49002.112            4
13 North 24038.870            5 North  13877.807            5
14 South  6353.078            5 South   2384.373            5
15 Total 30391.948            5 Total  16262.180            5
16 North 27844.266            6 North  10877.678            6
17 South  6658.389            6 South   4384.059            6
18 Total 34502.655            6 Total  15261.737            6
19 North 17157.443            7 North   9613.602            7
20 South  2606.327            7 South   6647.420            7
21 Total 19763.770            7 Total  16261.022            7
22 North 21095.366            8 North  16901.738            8
23 South  4268.078            8 South   4995.280            8
24 Total 25363.445            8 Total  21897.017            8
25 North 16762.802            9 North  25957.748            9
26 South  6842.953            9 South   4316.337            9
27 Total 23605.755            9 Total  30274.084            9
28 North 24327.593           10 North  23015.386           10
29 South  3457.492           10 South  15377.370           10
30 Total 27785.085           10 Total  38392.756           10

But setting seed:

set.seed(100)
easyboot <- bootdht(model=easy, flatfile=minke, nboot=10, cores = 3,
                    summary_fun = ex.N)
set.seed(100)
easyboot2 <- bootdht(model=easy, flatfile=minke, nboot=10, cores = 3,
                    summary_fun = ex.N)

Yields:

> cbind(easyboot, easyboot2)
   Label      Dhat bootstrap_ID Label      Dhat bootstrap_ID
1  North 27356.829            1 North 27356.829            1
2  South  7740.624            1 South  7740.624            1
3  Total 35097.453            1 Total 35097.453            1
4  North 20019.200            2 North 20019.200            2
5  South  8947.576            2 South  8947.576            2
6  Total 28966.776            2 Total 28966.776            2
7  North 15900.905            3 North 15900.905            3
8  South  1066.180            3 South  1066.180            3
9  Total 16967.085            3 Total 16967.085            3
10 North 30432.876            4 North 30432.876            4
11 South  7673.825            4 South  7673.825            4
12 Total 38106.701            4 Total 38106.701            4
13 North 21916.181            5 North 21916.181            5
14 South 10754.574            5 South 10754.574            5
15 Total 32670.755            5 Total 32670.755            5
16 North 12337.920            6 North 12337.920            6
17 South  6917.687            6 South  6917.687            6
18 Total 19255.608            6 Total 19255.608            6
19 North 22634.354            7 North 22634.354            7
20 South  5543.670            7 South  5543.670            7
21 Total 28178.023            7 Total 28178.023            7
22 North 30111.507            8 North 30111.507            8
23 South  7806.416            8 South  7806.416            8
24 Total 37917.923            8 Total 37917.923            8
25 North 18790.467            9 North 18790.467            9
26 South  4328.954            9 South  4328.954            9
27 Total 23119.421            9 Total 23119.421            9
28 North 16058.240           10 North 16058.240           10
29 South  5702.957           10 South  5702.957           10
30 Total 21761.197           10 Total 21761.197           10