CRAN Package Check Results for Package AlgDesign

Last updated on 2020-02-21 17:47:40 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2.0 10.29 36.78 47.07 OK
r-devel-linux-x86_64-debian-gcc 1.2.0 5.88 29.33 35.21 OK
r-devel-linux-x86_64-fedora-clang 1.2.0 60.13 NOTE
r-devel-linux-x86_64-fedora-gcc 1.2.0 55.66 NOTE
r-devel-windows-ix86+x86_64 1.2.0 16.00 54.00 70.00 ERROR
r-devel-windows-ix86+x86_64-gcc8 1.2.0 21.00 71.00 92.00 ERROR
r-patched-linux-x86_64 1.2.0 5.61 34.74 40.35 OK
r-patched-solaris-x86 1.2.0 81.20 OK
r-release-linux-x86_64 1.2.0 4.97 34.94 39.91 OK
r-release-windows-ix86+x86_64 1.2.0 23.00 77.00 100.00 OK
r-release-osx-x86_64 1.2.0 OK
r-oldrel-windows-ix86+x86_64 1.2.0 16.00 85.00 101.00 OK
r-oldrel-osx-x86_64 1.2.0 OK

Check Details

Version: 1.2.0
Check: compiled code
Result: NOTE
    File ‘AlgDesign/libs/AlgDesign.so’:
     Found no calls to: ‘R_registerRoutines’, ‘R_useDynamicSymbols’
    
    It is good practice to register native routines and to disable symbol
    search.
    
    See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 1.2.0
Check: running examples for arch ‘x64’
Result: ERROR
    Running examples in 'AlgDesign-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: optBlock
    > ### Title: Optimal design blocking
    > ### Aliases: optBlock
    > ### Keywords: design
    >
    > ### ** Examples
    >
    > # Blocking the design for a quadratic polynomial in three variables into two
    > # seven trial blocks:
    >
    > dat<-gen.factorial(3,3,varNames=c("A","B","C"))
    > desD<-optFederov(~quad(.),dat,nTrials=14,eval=TRUE) # Choose an optimum 14 trail design.
    > optBlock(~quad(.),desD$design,c(7,7))
    $D
    [1] 0.4178207
    
    $diagonality
    [1] 0.969
    
    $Blocks
    $Blocks$B1
     A B C
    1 -1 -1 -1
    6 1 0 -1
    8 0 1 -1
    18 1 1 0
    19 -1 -1 1
    21 1 -1 1
    25 -1 1 1
    
    $Blocks$B2
     A B C
    3 1 -1 -1
    7 -1 1 -1
    9 1 1 -1
    11 0 -1 0
    13 -1 0 0
    23 0 0 1
    27 1 1 1
    
    
    $design
     A B C
    1 -1 -1 -1
    6 1 0 -1
    8 0 1 -1
    18 1 1 0
    19 -1 -1 1
    21 1 -1 1
    25 -1 1 1
    3 1 -1 -1
    7 -1 1 -1
    9 1 1 -1
    11 0 -1 0
    13 -1 0 0
    23 0 0 1
    27 1 1 1
    
    $rows
     [1] 1 6 8 18 19 21 25 3 7 9 11 13 23 27
    
    >
    > # Letting optBlock() search the dat candidate list instead of first choosing a
    > # 14 trial design.
    > optBlock(~quad(.),dat,c(7,7))
    $D
    [1] 0.42645
    
    $diagonality
    [1] 0.927
    
    $Blocks
    $Blocks$B1
     A B C
    1 -1 -1 -1
    3 1 -1 -1
    6 1 0 -1
    7 -1 1 -1
    9 1 1 -1
    21 1 -1 1
    25 -1 1 1
    
    $Blocks$B2
     A B C
    2 0 -1 -1
    4 -1 0 -1
    8 0 1 -1
    16 -1 1 0
    18 1 1 0
    19 -1 -1 1
    27 1 1 1
    
    
    $design
     A B C
    1 -1 -1 -1
    3 1 -1 -1
    6 1 0 -1
    7 -1 1 -1
    9 1 1 -1
    21 1 -1 1
    25 -1 1 1
    2 0 -1 -1
    4 -1 0 -1
    8 0 1 -1
    16 -1 1 0
    18 1 1 0
    19 -1 -1 1
    27 1 1 1
    
    $rows
     [1] 1 3 6 7 9 21 25 2 4 8 16 18 19 27
    
    >
    >
    > # A block design for 7 treatments in 7 blocks of size 3. Note how withinData
    > # is recycled to fill out the blocksize requirements.
    >
    > BIB<-optBlock(~.,withinData=factor(1:7),blocksizes=rep(3,7))
    >
    > # This is a balanced incomplete block design as may be seen from:
    >
    > crossprod(table(BIB$rows,c(rep(1:7, rep(3,7)))))
    
     1 2 3 4 5 6 7
     1 3 1 1 1 1 1 1
     2 1 3 1 1 1 1 1
     3 1 1 3 1 1 1 1
     4 1 1 1 3 1 1 1
     5 1 1 1 1 3 1 1
     6 1 1 1 1 1 3 1
     7 1 1 1 1 1 1 3
    >
    > # A partially balanced incomplete block design with two associate classes:
    >
    > tr<-factor(1:9)
    > PBIB<-optBlock(~.,withinData=tr,blocksizes=rep(3,9))
    >
    > crossprod(table(PBIB$rows,c(rep(1:9, rep(3,9)))))
    
     1 2 3 4 5 6 7 8 9
     1 3 0 1 0 1 1 1 1 1
     2 0 3 1 0 1 1 1 1 1
     3 1 1 3 1 0 0 1 1 1
     4 0 0 1 3 1 1 1 1 1
     5 1 1 0 1 3 0 1 1 1
     6 1 1 0 1 0 3 1 1 1
     7 1 1 1 1 1 1 3 0 0
     8 1 1 1 1 1 1 0 3 0
     9 1 1 1 1 1 1 0 0 3
    >
    >
    > # Two fractions of a 2^(4-1).
    >
    > dat<-gen.factorial(2,4)
    > od<-optBlock(~.,dat,c(8,8))
    >
    > # The blocks are not themselves orthogonal even though the entire design is optimal.
    >
    > bk<-data.matrix(od$Blocks$B1)
    > t(bk)%*%bk
     X1 X2 X3 X4
    X1 8 0 -4 0
    X2 0 8 4 0
    X3 -4 4 8 -4
    X4 0 0 -4 8
    >
    > # Better blocks may be obtained as follows, but note that they are not generally
    > # the fractions that would be obtained by confounding the third order interaction.
    >
    > od<-optBlock(~.,dat,c(8,8),criterion="Dpc",nR=10)
    > bk<-data.matrix(od$Blocks$B1)
    > t(bk)%*%bk
     X1 X2 X3 X4
    X1 8 0 0 0
    X2 0 8 0 0
    X3 0 0 8 0
    X4 0 0 0 8
    >
    > # Blocking with whole plot factors. Note that the 27 rows of within are recycled
    > # to make the 54 trial blocked design.
    >
    > within<-expand.grid(A=c(-1,0,1),B=c(-1,0,1),C=c(-1,0,1))
    > whole<-expand.grid(D=factor(1:3),E=factor(1:3))
    > od<-optBlock(~D+E*(quad(A,B,C)),withinData=within,blocksizes=rep(6,9),wholeBlockData=whole)
    >
    > # Either withinData, or wholeBlockData may be an approximate theory optimial design
    > # produced by optFederov() for nTrials. The first column in the optFederov() output
    > # design, named "Rep..", is used to replicate the trials.
    >
    > within<-optFederov(~quad(A,B,C),within,nT=54,approx=TRUE)
    > od<-optBlock(~D+E*(quad(A,B,C)),withinData=within$design,blocksizes=rep(6,9),wholeBlockData=whole)
    Error in terms.formula(object, data = data) :
     invalid type (builtin) for 'dimnames' (must be a vector)
    Calls: optBlock ... model.matrix.formula -> model.matrix.default -> terms -> terms.formula
    Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8