example1: Examples 1 and 3 of Kulinskaya and Lewin

In fuzzyFDR: Exact calculation of fuzzy decision rules for multiple testing

Description

Observed and previously attainable p-values used in Examples 1 and 3 of Kulinskaya and Lewin.

Usage

data(example1)

Format

A data frame with 7 observations on the following 2 variables.

pvals

a numeric vector

pprev

a numeric vector

Source

Kulinskaya and Lewin (2007).

Examples

data(example1)
fuzzyBHexact(example1$pvals,example1$pprev,alpha=0.05)

Example output

[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

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