CRAN Package Check Results for Package finalfit

Last updated on 2020-06-07 06:46:45 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.1 13.89 288.97 302.86 ERROR
r-devel-linux-x86_64-debian-gcc 1.0.1 12.57 219.57 232.14 ERROR
r-devel-linux-x86_64-fedora-clang 1.0.1 382.92 ERROR
r-devel-linux-x86_64-fedora-gcc 1.0.1 373.44 ERROR
r-devel-windows-ix86+x86_64 1.0.1 47.00 386.00 433.00 ERROR
r-patched-linux-x86_64 1.0.1 15.49 284.25 299.74 ERROR
r-patched-solaris-x86 1.0.1 494.20 ERROR
r-release-linux-x86_64 1.0.1 15.80 286.85 302.65 ERROR
r-release-osx-x86_64 1.0.1 OK
r-release-windows-ix86+x86_64 1.0.1 41.00 405.00 446.00 ERROR
r-oldrel-osx-x86_64 1.0.1 OK
r-oldrel-windows-ix86+x86_64 1.0.1 38.00 389.00 427.00 ERROR

Check Details

Version: 1.0.1
Check: examples
Result: ERROR
    Running examples in 'finalfit-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: check_recode
    > ### Title: Check accurate recoding of variables
    > ### Aliases: check_recode
    >
    > ### ** Examples
    >
    > library(dplyr)
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    > data(colon_s)
    > colon_s_small = colon_s %>%
    + select(-id, -rx, -rx.factor) %>%
    + mutate(
    + age.factor2 = forcats::fct_collapse(age.factor,
    + "<60 years" = c("<40 years", "40-59 years")),
    + sex.factor2 = forcats::fct_recode(sex.factor,
    + # Intentional miscode
    + "F" = "Male",
    + "M" = "Female")
    + )
    >
    > # Check
    > colon_s_small %>%
    + check_recode(include_numerics = FALSE)
    $index
    # A tibble: 3 x 2
     var1 var2
     <chr> <chr>
    1 sex.factor sex.factor2
    2 age.factor age.factor2
    3 sex.factor2 age.factor2
    
    $counts
    $counts[[1]]
     sex.factor sex.factor2 n
    1 Female M 445
    2 Male F 484
    
    $counts[[2]]
     age.factor age.factor2 n
    1 <40 years <60 years 70
    2 40-59 years <60 years 344
    3 60+ years 60+ years 515
    
    $counts[[3]]
     sex.factor2 age.factor2 n
    1 M <60 years 204
    2 M 60+ years 241
    3 F <60 years 210
    4 F 60+ years 274
    
    
    >
    > out = colon_s_small %>%
    + select(-extent, -extent.factor,-time, -time.years) %>%
    + check_recode()
    > out
    $index
    # A tibble: 19 x 2
     var1 var2
     <chr> <chr>
     1 sex sex.factor
     2 sex sex.factor2
     3 age age.factor
     4 age age.10
     5 age age.factor2
     6 obstruct obstruct.factor
     7 perfor perfor.factor
     8 adhere adhere.factor
     9 nodes node4
    10 nodes node4.factor
    11 status status.factor
    12 differ differ.factor
    13 surg surg.factor
    14 node4 node4.factor
    15 sex.factor sex.factor2
    16 age.factor age.factor2
    17 loccomp loccomp.factor
    18 mort_5yr mort_5yr.num
    19 sex.factor2 age.factor2
    
    $counts
    $counts[[1]]
     sex sex.factor n
    1 0 Female 445
    2 1 Male 484
    
    $counts[[2]]
     sex sex.factor2 n
    1 0 M 445
    2 1 F 484
    
    $counts[[3]]
     age age.factor n
    1 18 <40 years 1
    2 22 <40 years 1
    3 25 <40 years 1
    4 26 <40 years 1
    5 27 <40 years 3
    6 28 <40 years 1
    7 29 <40 years 1
    8 30 <40 years 5
    9 31 <40 years 2
    10 32 <40 years 5
    11 33 <40 years 7
    12 34 <40 years 4
    13 35 <40 years 2
    14 36 <40 years 10
    15 37 <40 years 2
    16 38 <40 years 10
    17 39 <40 years 14
    18 40 40-59 years 8
    19 41 40-59 years 7
    20 42 40-59 years 7
    21 43 40-59 years 11
    22 44 40-59 years 8
    23 45 40-59 years 13
    24 46 40-59 years 19
    25 47 40-59 years 12
    26 48 40-59 years 15
    27 49 40-59 years 13
    28 50 40-59 years 14
    29 51 40-59 years 10
    30 52 40-59 years 20
    31 53 40-59 years 22
    32 54 40-59 years 16
    33 55 40-59 years 27
    34 56 40-59 years 31
    35 57 40-59 years 31
    36 58 40-59 years 29
    37 59 40-59 years 31
    38 60 60+ years 31
    39 61 60+ years 36
    40 62 60+ years 21
    41 63 60+ years 29
    42 64 60+ years 36
    43 65 60+ years 28
    44 66 60+ years 35
    45 67 60+ years 24
    46 68 60+ years 38
    47 69 60+ years 20
    48 70 60+ years 36
    49 71 60+ years 24
    50 72 60+ years 25
    51 73 60+ years 20
    52 74 60+ years 34
    53 75 60+ years 17
    54 76 60+ years 21
    55 77 60+ years 11
    56 78 60+ years 5
    57 79 60+ years 7
    58 80 60+ years 8
    59 81 60+ years 5
    60 82 60+ years 2
    61 83 60+ years 1
    62 85 60+ years 1
    
    $counts[[4]]
     age age.10 n
    1 18 1.8 1
    2 22 2.2 1
    3 25 2.5 1
    4 26 2.6 1
    5 27 2.7 3
    6 28 2.8 1
    7 29 2.9 1
    8 30 3.0 5
    9 31 3.1 2
    10 32 3.2 5
    11 33 3.3 7
    12 34 3.4 4
    13 35 3.5 2
    14 36 3.6 10
    15 37 3.7 2
    16 38 3.8 10
    17 39 3.9 14
    18 40 4.0 8
    19 41 4.1 7
    20 42 4.2 7
    21 43 4.3 11
    22 44 4.4 8
    23 45 4.5 13
    24 46 4.6 19
    25 47 4.7 12
    26 48 4.8 15
    27 49 4.9 13
    28 50 5.0 14
    29 51 5.1 10
    30 52 5.2 20
    31 53 5.3 22
    32 54 5.4 16
    33 55 5.5 27
    34 56 5.6 31
    35 57 5.7 31
    36 58 5.8 29
    37 59 5.9 31
    38 60 6.0 31
    39 61 6.1 36
    40 62 6.2 21
    41 63 6.3 29
    42 64 6.4 36
    43 65 6.5 28
    44 66 6.6 35
    45 67 6.7 24
    46 68 6.8 38
    47 69 6.9 20
    48 70 7.0 36
    49 71 7.1 24
    50 72 7.2 25
    51 73 7.3 20
    52 74 7.4 34
    53 75 7.5 17
    54 76 7.6 21
    55 77 7.7 11
    56 78 7.8 5
    57 79 7.9 7
    58 80 8.0 8
    59 81 8.1 5
    60 82 8.2 2
    61 83 8.3 1
    62 85 8.5 1
    
    $counts[[5]]
     age age.factor2 n
    1 18 <60 years 1
    2 22 <60 years 1
    3 25 <60 years 1
    4 26 <60 years 1
    5 27 <60 years 3
    6 28 <60 years 1
    7 29 <60 years 1
    8 30 <60 years 5
    9 31 <60 years 2
    10 32 <60 years 5
    11 33 <60 years 7
    12 34 <60 years 4
    13 35 <60 years 2
    14 36 <60 years 10
    15 37 <60 years 2
    16 38 <60 years 10
    17 39 <60 years 14
    18 40 <60 years 8
    19 41 <60 years 7
    20 42 <60 years 7
    21 43 <60 years 11
    22 44 <60 years 8
    23 45 <60 years 13
    24 46 <60 years 19
    25 47 <60 years 12
    26 48 <60 years 15
    27 49 <60 years 13
    28 50 <60 years 14
    29 51 <60 years 10
    30 52 <60 years 20
    31 53 <60 years 22
    32 54 <60 years 16
    33 55 <60 years 27
    34 56 <60 years 31
    35 57 <60 years 31
    36 58 <60 years 29
    37 59 <60 years 31
    38 60 60+ years 31
    39 61 60+ years 36
    40 62 60+ years 21
    41 63 60+ years 29
    42 64 60+ years 36
    43 65 60+ years 28
    44 66 60+ years 35
    45 67 60+ years 24
    46 68 60+ years 38
    47 69 60+ years 20
    48 70 60+ years 36
    49 71 60+ years 24
    50 72 60+ years 25
    51 73 60+ years 20
    52 74 60+ years 34
    53 75 60+ years 17
    54 76 60+ years 21
    55 77 60+ years 11
    56 78 60+ years 5
    57 79 60+ years 7
    58 80 60+ years 8
    59 81 60+ years 5
    60 82 60+ years 2
    61 83 60+ years 1
    62 85 60+ years 1
    
    $counts[[6]]
     obstruct obstruct.factor n
    1 0 No 732
    2 1 Yes 176
    3 NA <NA> 21
    
    $counts[[7]]
     perfor perfor.factor n
    1 0 No 902
    2 1 Yes 27
    
    $counts[[8]]
     adhere adhere.factor n
    1 0 No 794
    2 1 Yes 135
    
    $counts[[9]]
     nodes node4 n
    1 0 0 2
    2 1 0 269
    3 1 1 5
    4 2 0 194
    5 3 0 124
    6 3 1 1
    7 4 0 81
    8 4 1 3
    9 5 0 1
    10 5 1 45
    11 6 1 43
    12 7 1 38
    13 8 0 1
    14 8 1 22
    15 9 0 1
    16 9 1 19
    17 10 1 13
    18 11 1 10
    19 12 1 11
    20 13 1 7
    21 14 1 4
    22 15 1 6
    23 16 1 1
    24 17 1 2
    25 19 1 2
    26 20 1 2
    27 22 1 1
    28 24 1 1
    29 27 1 1
    30 33 1 1
    31 NA 0 1
    32 NA 1 17
    
    $counts[[10]]
     nodes node4.factor n
    1 0 No 2
    2 1 No 269
    3 1 Yes 5
    4 2 No 194
    5 3 No 124
    6 3 Yes 1
    7 4 No 81
    8 4 Yes 3
    9 5 No 1
    10 5 Yes 45
    11 6 Yes 43
    12 7 Yes 38
    13 8 No 1
    14 8 Yes 22
    15 9 No 1
    16 9 Yes 19
    17 10 Yes 13
    18 11 Yes 10
    19 12 Yes 11
    20 13 Yes 7
    21 14 Yes 4
    22 15 Yes 6
    23 16 Yes 1
    24 17 Yes 2
    25 19 Yes 2
    26 20 Yes 2
    27 22 Yes 1
    28 24 Yes 1
    29 27 Yes 1
    30 33 Yes 1
    31 NA No 1
    32 NA Yes 17
    
    $counts[[11]]
     status status.factor n
    1 0 Alive 477
    2 1 Died 452
    
    $counts[[12]]
     differ differ.factor n
    1 1 Well 93
    2 2 Moderate 663
    3 3 Poor 150
    4 NA <NA> 23
    
    $counts[[13]]
     surg surg.factor n
    1 0 Short 668
    2 1 Long 244
    3 NA <NA> 17
    
    $counts[[14]]
     node4 node4.factor n
    1 0 No 674
    2 1 Yes 255
    
    $counts[[15]]
     sex.factor sex.factor2 n
    1 Female M 445
    2 Male F 484
    
    $counts[[16]]
     age.factor age.factor2 n
    1 <40 years <60 years 70
    2 40-59 years <60 years 344
    3 60+ years 60+ years 515
    
    $counts[[17]]
     loccomp loccomp.factor n
    1 0 No 616
    2 1 Yes 293
    3 NA <NA> 20
    
    $counts[[18]]
     mort_5yr mort_5yr.num n
    1 Alive 1 511
    2 Died 2 404
    3 <NA> NA 14
    
    $counts[[19]]
     sex.factor2 age.factor2 n
    1 M <60 years 204
    2 M 60+ years 241
    3 F <60 years 210
    4 F 60+ years 274
    
    
    >
    > # Select a tibble and expand
    > out$counts[[9]] %>%
    + print(n = Inf)
    Error in print.default(m, ..., quote = quote, right = right, max = max) :
     invalid 'na.print' specification
    Calls: %>% ... print -> print.data.frame -> print -> print.default
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 1.0.1
Check: examples
Result: ERROR
    Running examples in ‘finalfit-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: check_recode
    > ### Title: Check accurate recoding of variables
    > ### Aliases: check_recode
    >
    > ### ** Examples
    >
    > library(dplyr)
    
    Attaching package: ‘dplyr’
    
    The following objects are masked from ‘package:stats’:
    
     filter, lag
    
    The following objects are masked from ‘package:base’:
    
     intersect, setdiff, setequal, union
    
    > data(colon_s)
    > colon_s_small = colon_s %>%
    + select(-id, -rx, -rx.factor) %>%
    + mutate(
    + age.factor2 = forcats::fct_collapse(age.factor,
    + "<60 years" = c("<40 years", "40-59 years")),
    + sex.factor2 = forcats::fct_recode(sex.factor,
    + # Intentional miscode
    + "F" = "Male",
    + "M" = "Female")
    + )
    >
    > # Check
    > colon_s_small %>%
    + check_recode(include_numerics = FALSE)
    $index
    # A tibble: 3 x 2
     var1 var2
     <chr> <chr>
    1 sex.factor sex.factor2
    2 age.factor age.factor2
    3 sex.factor2 age.factor2
    
    $counts
    $counts[[1]]
     sex.factor sex.factor2 n
    1 Female M 445
    2 Male F 484
    
    $counts[[2]]
     age.factor age.factor2 n
    1 <40 years <60 years 70
    2 40-59 years <60 years 344
    3 60+ years 60+ years 515
    
    $counts[[3]]
     sex.factor2 age.factor2 n
    1 M <60 years 204
    2 M 60+ years 241
    3 F <60 years 210
    4 F 60+ years 274
    
    
    >
    > out = colon_s_small %>%
    + select(-extent, -extent.factor,-time, -time.years) %>%
    + check_recode()
    > out
    $index
    # A tibble: 19 x 2
     var1 var2
     <chr> <chr>
     1 sex sex.factor
     2 sex sex.factor2
     3 age age.factor
     4 age age.10
     5 age age.factor2
     6 obstruct obstruct.factor
     7 perfor perfor.factor
     8 adhere adhere.factor
     9 nodes node4
    10 nodes node4.factor
    11 status status.factor
    12 differ differ.factor
    13 surg surg.factor
    14 node4 node4.factor
    15 sex.factor sex.factor2
    16 age.factor age.factor2
    17 loccomp loccomp.factor
    18 mort_5yr mort_5yr.num
    19 sex.factor2 age.factor2
    
    $counts
    $counts[[1]]
     sex sex.factor n
    1 0 Female 445
    2 1 Male 484
    
    $counts[[2]]
     sex sex.factor2 n
    1 0 M 445
    2 1 F 484
    
    $counts[[3]]
     age age.factor n
    1 18 <40 years 1
    2 22 <40 years 1
    3 25 <40 years 1
    4 26 <40 years 1
    5 27 <40 years 3
    6 28 <40 years 1
    7 29 <40 years 1
    8 30 <40 years 5
    9 31 <40 years 2
    10 32 <40 years 5
    11 33 <40 years 7
    12 34 <40 years 4
    13 35 <40 years 2
    14 36 <40 years 10
    15 37 <40 years 2
    16 38 <40 years 10
    17 39 <40 years 14
    18 40 40-59 years 8
    19 41 40-59 years 7
    20 42 40-59 years 7
    21 43 40-59 years 11
    22 44 40-59 years 8
    23 45 40-59 years 13
    24 46 40-59 years 19
    25 47 40-59 years 12
    26 48 40-59 years 15
    27 49 40-59 years 13
    28 50 40-59 years 14
    29 51 40-59 years 10
    30 52 40-59 years 20
    31 53 40-59 years 22
    32 54 40-59 years 16
    33 55 40-59 years 27
    34 56 40-59 years 31
    35 57 40-59 years 31
    36 58 40-59 years 29
    37 59 40-59 years 31
    38 60 60+ years 31
    39 61 60+ years 36
    40 62 60+ years 21
    41 63 60+ years 29
    42 64 60+ years 36
    43 65 60+ years 28
    44 66 60+ years 35
    45 67 60+ years 24
    46 68 60+ years 38
    47 69 60+ years 20
    48 70 60+ years 36
    49 71 60+ years 24
    50 72 60+ years 25
    51 73 60+ years 20
    52 74 60+ years 34
    53 75 60+ years 17
    54 76 60+ years 21
    55 77 60+ years 11
    56 78 60+ years 5
    57 79 60+ years 7
    58 80 60+ years 8
    59 81 60+ years 5
    60 82 60+ years 2
    61 83 60+ years 1
    62 85 60+ years 1
    
    $counts[[4]]
     age age.10 n
    1 18 1.8 1
    2 22 2.2 1
    3 25 2.5 1
    4 26 2.6 1
    5 27 2.7 3
    6 28 2.8 1
    7 29 2.9 1
    8 30 3.0 5
    9 31 3.1 2
    10 32 3.2 5
    11 33 3.3 7
    12 34 3.4 4
    13 35 3.5 2
    14 36 3.6 10
    15 37 3.7 2
    16 38 3.8 10
    17 39 3.9 14
    18 40 4.0 8
    19 41 4.1 7
    20 42 4.2 7
    21 43 4.3 11
    22 44 4.4 8
    23 45 4.5 13
    24 46 4.6 19
    25 47 4.7 12
    26 48 4.8 15
    27 49 4.9 13
    28 50 5.0 14
    29 51 5.1 10
    30 52 5.2 20
    31 53 5.3 22
    32 54 5.4 16
    33 55 5.5 27
    34 56 5.6 31
    35 57 5.7 31
    36 58 5.8 29
    37 59 5.9 31
    38 60 6.0 31
    39 61 6.1 36
    40 62 6.2 21
    41 63 6.3 29
    42 64 6.4 36
    43 65 6.5 28
    44 66 6.6 35
    45 67 6.7 24
    46 68 6.8 38
    47 69 6.9 20
    48 70 7.0 36
    49 71 7.1 24
    50 72 7.2 25
    51 73 7.3 20
    52 74 7.4 34
    53 75 7.5 17
    54 76 7.6 21
    55 77 7.7 11
    56 78 7.8 5
    57 79 7.9 7
    58 80 8.0 8
    59 81 8.1 5
    60 82 8.2 2
    61 83 8.3 1
    62 85 8.5 1
    
    $counts[[5]]
     age age.factor2 n
    1 18 <60 years 1
    2 22 <60 years 1
    3 25 <60 years 1
    4 26 <60 years 1
    5 27 <60 years 3
    6 28 <60 years 1
    7 29 <60 years 1
    8 30 <60 years 5
    9 31 <60 years 2
    10 32 <60 years 5
    11 33 <60 years 7
    12 34 <60 years 4
    13 35 <60 years 2
    14 36 <60 years 10
    15 37 <60 years 2
    16 38 <60 years 10
    17 39 <60 years 14
    18 40 <60 years 8
    19 41 <60 years 7
    20 42 <60 years 7
    21 43 <60 years 11
    22 44 <60 years 8
    23 45 <60 years 13
    24 46 <60 years 19
    25 47 <60 years 12
    26 48 <60 years 15
    27 49 <60 years 13
    28 50 <60 years 14
    29 51 <60 years 10
    30 52 <60 years 20
    31 53 <60 years 22
    32 54 <60 years 16
    33 55 <60 years 27
    34 56 <60 years 31
    35 57 <60 years 31
    36 58 <60 years 29
    37 59 <60 years 31
    38 60 60+ years 31
    39 61 60+ years 36
    40 62 60+ years 21
    41 63 60+ years 29
    42 64 60+ years 36
    43 65 60+ years 28
    44 66 60+ years 35
    45 67 60+ years 24
    46 68 60+ years 38
    47 69 60+ years 20
    48 70 60+ years 36
    49 71 60+ years 24
    50 72 60+ years 25
    51 73 60+ years 20
    52 74 60+ years 34
    53 75 60+ years 17
    54 76 60+ years 21
    55 77 60+ years 11
    56 78 60+ years 5
    57 79 60+ years 7
    58 80 60+ years 8
    59 81 60+ years 5
    60 82 60+ years 2
    61 83 60+ years 1
    62 85 60+ years 1
    
    $counts[[6]]
     obstruct obstruct.factor n
    1 0 No 732
    2 1 Yes 176
    3 NA <NA> 21
    
    $counts[[7]]
     perfor perfor.factor n
    1 0 No 902
    2 1 Yes 27
    
    $counts[[8]]
     adhere adhere.factor n
    1 0 No 794
    2 1 Yes 135
    
    $counts[[9]]
     nodes node4 n
    1 0 0 2
    2 1 0 269
    3 1 1 5
    4 2 0 194
    5 3 0 124
    6 3 1 1
    7 4 0 81
    8 4 1 3
    9 5 0 1
    10 5 1 45
    11 6 1 43
    12 7 1 38
    13 8 0 1
    14 8 1 22
    15 9 0 1
    16 9 1 19
    17 10 1 13
    18 11 1 10
    19 12 1 11
    20 13 1 7
    21 14 1 4
    22 15 1 6
    23 16 1 1
    24 17 1 2
    25 19 1 2
    26 20 1 2
    27 22 1 1
    28 24 1 1
    29 27 1 1
    30 33 1 1
    31 NA 0 1
    32 NA 1 17
    
    $counts[[10]]
     nodes node4.factor n
    1 0 No 2
    2 1 No 269
    3 1 Yes 5
    4 2 No 194
    5 3 No 124
    6 3 Yes 1
    7 4 No 81
    8 4 Yes 3
    9 5 No 1
    10 5 Yes 45
    11 6 Yes 43
    12 7 Yes 38
    13 8 No 1
    14 8 Yes 22
    15 9 No 1
    16 9 Yes 19
    17 10 Yes 13
    18 11 Yes 10
    19 12 Yes 11
    20 13 Yes 7
    21 14 Yes 4
    22 15 Yes 6
    23 16 Yes 1
    24 17 Yes 2
    25 19 Yes 2
    26 20 Yes 2
    27 22 Yes 1
    28 24 Yes 1
    29 27 Yes 1
    30 33 Yes 1
    31 NA No 1
    32 NA Yes 17
    
    $counts[[11]]
     status status.factor n
    1 0 Alive 477
    2 1 Died 452
    
    $counts[[12]]
     differ differ.factor n
    1 1 Well 93
    2 2 Moderate 663
    3 3 Poor 150
    4 NA <NA> 23
    
    $counts[[13]]
     surg surg.factor n
    1 0 Short 668
    2 1 Long 244
    3 NA <NA> 17
    
    $counts[[14]]
     node4 node4.factor n
    1 0 No 674
    2 1 Yes 255
    
    $counts[[15]]
     sex.factor sex.factor2 n
    1 Female M 445
    2 Male F 484
    
    $counts[[16]]
     age.factor age.factor2 n
    1 <40 years <60 years 70
    2 40-59 years <60 years 344
    3 60+ years 60+ years 515
    
    $counts[[17]]
     loccomp loccomp.factor n
    1 0 No 616
    2 1 Yes 293
    3 NA <NA> 20
    
    $counts[[18]]
     mort_5yr mort_5yr.num n
    1 Alive 1 511
    2 Died 2 404
    3 <NA> NA 14
    
    $counts[[19]]
     sex.factor2 age.factor2 n
    1 M <60 years 204
    2 M 60+ years 241
    3 F <60 years 210
    4 F 60+ years 274
    
    
    >
    > # Select a tibble and expand
    > out$counts[[9]] %>%
    + print(n = Inf)
    Error in print.default(m, ..., quote = quote, right = right, max = max) :
     invalid 'na.print' specification
    Calls: %>% ... print -> print.data.frame -> print -> print.default
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-solaris-x86, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 1.0.1
Check: installed package size
Result: NOTE
     installed size is 5.3Mb
     sub-directories of 1Mb or more:
     doc 4.5Mb
Flavor: r-patched-solaris-x86