fuzzyFDR-package: Exact calculation of fuzzy decision rules for multiple...

Description Details Author(s) References Examples

Description

Exact calculation of fuzzy decision rules for multiple testing. Choose to control FDR (false discovery rate) using the Benjamini and Hochberg method, or FWER (family wise error rate) using the Bonferroni method. Kulinsakaya and Lewin (2007).

Details

Package: fuzzyFDR
Type: Package
Version: 1.0
Date: 2007-10-16
License: GPL

~~ An overview of how to use the package, including the most important functions ~~

Author(s)

Alex Lewin Maintainer: Alex Lewin <a.m.lewin@imperial.ac.uk>

References

Kulinsakaya and Lewin (2007).

Examples

1
2
3
4
5
6

Example output

[1] "pvals" "pprev"
[1] "total no. intervals =  8"
[1] "total no. possible alloc. =  1296"
[1] "global sf =  6"
[1] "global sc =  4"
  p.minus p.plus r.minus r.plus leng a.minus a.plus
1  0.0000 0.0010       1      2    2  0.0071 0.0143
2  0.0010 0.0039       1      3    3  0.0071 0.0214
3  0.0039 0.0107       2      4    3  0.0143 0.0286
4  0.0107 0.0156       3      5    3  0.0214 0.0357
5  0.0156 0.0352       4      6    3  0.0286 0.0429
6  0.0352 0.0547       5      7    3  0.0357 0.0500
7  0.0547 0.1094       6      7    2  0.0429 0.0500
8  0.1094 0.1445       7      7    1  0.0500 0.0500
[1] "reduced no. intervals =  4"
[1] "reduced no. alloc. =  36"
  new.p.minus new.p.plus new.r.minus new.r.plus
1      0.0000     0.0156           1          5
2      0.0156     0.0352           4          6
3      0.0352     0.0547           5          7
4      0.0547     0.1445           6          7
[1] "starting loop over allocations"
[1] ""
[1] "Exact Method"
[1] "alpha =  0.05"
   pvals  pprev z.min z.max new.z.min new.z.max    tau
1 0.0039 0.0000     1     2         1         1 1.0000
2 0.0107 0.0010     2     3         1         1 1.0000
3 0.0156 0.0000     1     4         1         1 1.0000
4 0.0352 0.0039     3     5         1         2 0.9340
5 0.0547 0.0107     4     6         1         3 0.6325
6 0.1094 0.0156     5     7         2         4 0.2815
7 0.1445 0.0352     6     8         3         4 0.0801
   pvals  pprev z.min z.max new.z.min new.z.max    tau
1 0.0039 0.0000     1     2         1         1 1.0000
2 0.0107 0.0010     2     3         1         1 1.0000
3 0.0156 0.0000     1     4         1         1 1.0000
4 0.0352 0.0039     3     5         1         2 0.9340
5 0.0547 0.0107     4     6         1         3 0.6325
6 0.1094 0.0156     5     7         2         4 0.2815
7 0.1445 0.0352     6     8         3         4 0.0801
[1] "pvals" "pprev"
[1] "total no. intervals =  4"
[1] "total no. possible alloc. =  1"
[1] "global sf =  2"
[1] "global sc =  1"
  p.minus p.plus r.minus r.plus leng a.minus a.plus
1   0.000  0.004       1      1    1   0.005  0.005
2   0.004  0.035       2      4    3   0.010  0.020
3   0.035  0.145       5      6    2   0.025  0.030
4   0.145  0.363       7     10    4   0.035  0.050
[1] "reduced no. intervals =  3"
[1] "reduced no. alloc. =  1"
  new.p.minus new.p.plus new.r.minus new.r.plus
1       0.000      0.004           1          1
2       0.004      0.035           2          4
3       0.035      0.363           5         10
[1] "starting loop over allocations"
[1] ""
[1] "Exact Method"
[1] "alpha =  0.05"
   pvals pprev z.min z.max new.z.min new.z.max    tau
1  0.004 0.000     1     1         1         1 1.0000
2  0.035 0.004     2     2         2         2 0.3349
3  0.035 0.004     2     2         2         2 0.3349
4  0.035 0.004     2     2         2         2 0.3349
5  0.145 0.035     3     3         3         3 0.0000
6  0.145 0.035     3     3         3         3 0.0000
7  0.363 0.145     4     4         3         3 0.0000
8  0.363 0.145     4     4         3         3 0.0000
9  0.363 0.145     4     4         3         3 0.0000
10 0.363 0.145     4     4         3         3 0.0000
   pvals pprev z.min z.max new.z.min new.z.max    tau
1  0.004 0.000     1     1         1         1 1.0000
2  0.035 0.004     2     2         2         2 0.3349
3  0.035 0.004     2     2         2         2 0.3349
4  0.035 0.004     2     2         2         2 0.3349
5  0.145 0.035     3     3         3         3 0.0000
6  0.145 0.035     3     3         3         3 0.0000
7  0.363 0.145     4     4         3         3 0.0000
8  0.363 0.145     4     4         3         3 0.0000
9  0.363 0.145     4     4         3         3 0.0000
10 0.363 0.145     4     4         3         3 0.0000

fuzzyFDR documentation built on May 2, 2019, 5:14 a.m.