* using log directory 'd:/Rcompile/CRANpkg/local/3.5/fracdiff.Rcheck'
* using R version 3.5.3 (2019-03-11)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* checking for file 'fracdiff/DESCRIPTION' ... OK
* this is package 'fracdiff' version '1.5-1'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'fracdiff' can be installed ... WARNING
Found the following significant warnings:
  Warning: unable to re-encode 'diffseries.R' line 42
See 'd:/Rcompile/CRANpkg/local/3.5/fracdiff.Rcheck/00install.out' for details.
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* loading checks for arch 'i386'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... OK
** checking use of S3 registration ... OK
* loading checks for arch 'x64'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... OK
** checking use of S3 registration ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [4s] OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking pragmas in C/C++ headers and code ... OK
* checking compiled code ... OK
* checking examples ...
** running examples for arch 'i386' ... [2s] OK
** running examples for arch 'x64' ... [2s] OK
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
** running tests for arch 'i386' ... [11s] ERROR
  Running 'Valderio-ex.R' [1s]
  Comparing 'Valderio-ex.Rout' to 'Valderio-ex.Rout.save' ... OK
  Running 'ex-Vinod.R' [0s]
  Running 'ex.R' [1s]
  Running 'sim-2.R' [1s]
  Running 'sim-ex.R' [6s]
  Comparing 'sim-ex.Rout' to 'sim-ex.Rout.save' ... OK
Running the tests in 'tests/ex.R' failed.
Complete output:
  > library(fracdiff)
  > 
  > doExtras <- interactive() # for now
  > 
  > .proctime00 <- proc.time()
  > 
  > set.seed(107)
  > options(digits = 5)
  > 
  > ## 1)
  > 
  > x1 <- fracdiff.sim(5000, ar = .2, ma = -.4, d = .3, n.start=0, allow.0 = TRUE)
  > (fd1 <- fracdiff(x1$series, nar = 1, nma = 1, dtol = 1e-10))
  
  Call:
    fracdiff(x = x1$series, nar = 1, nma = 1, dtol = 1e-10) 
  
  Coefficients:
         d       ar       ma 
   0.26721  0.27824 -0.36951 
  sigma[eps] = 0.99138 
  a list with components:
   [1] "log.likelihood"  "n"               "msg"             "d"              
   [5] "ar"              "ma"              "covariance.dpq"  "fnormMin"       
   [9] "sigma"           "stderror.dpq"    "correlation.dpq" "h"              
  [13] "d.tol"           "M"               "hessian.dpq"     "length.w"       
  [17] "residuals"       "fitted"          "call"           
  > vcov(fd1)
                d         ar1         ma1
  d    0.00059661 -0.00080522 -0.00018971
  ar1 -0.00080522  0.00161219  0.00066399
  ma1 -0.00018971  0.00066399  0.00054849
  > logLik(fd1)
  'log Lik.' -7051.5 (df=4)
  > 
  > fdCOVcomp <-
  +     c("h", "covariance.dpq", "stderror.dpq", "correlation.dpq", "hessian.dpq")
  > fd1. <- fracdiff.var(x1$series, fd1, h = fd1$h / 2)
  > dns <- dimnames(fd1.$covariance.dpq)
  > 
  > ## dput(sapply(fd1.[fdCOVcomp], signif, digits = 4)) # edited:
  > fd1.L <- list(
  +     h = 3.7155e-05,
  +     covariance.dpq = matrix(c(0.0005966, -0.0008052, -0.0001897,
  +                               -0.0008052, 0.001612, 0.000664,
  +                               -0.0001897, 0.000664, 0.0005485),
  +                             3L, 3L, dimnames = dns),
  +     stderror.dpq = c(0.02443, 0.04015, 0.02342),
  +     correlation.dpq = matrix(c(1, -0.821, -0.3316,
  +                                -0.821, 1,  0.7061,
  +                                -0.3316, 0.7061, 1), 3),
  +     hessian.dpq = matrix(c(-8252, -5875, 4258,
  +                            -5875, -5420, 4529,
  +                            4258, 4529, -5834),
  +                          3L, 3L, dimnames = dns))
  > stopifnot(all.equal(fd1.[fdCOVcomp], fd1.L, tolerance = 2e-4))
  > 
  > fd1u <- fracdiff.var(x1$series, fd1, h = fd1$h * 8)
  > ## dput(sapply(fd1u[fdCOVcomp], signif, digits = 4)) :
  > fd1uL <- list(
  +     h = 0.0005945,
  +     covariance.dpq = matrix(c(0.0005966, -0.0008052, -0.0001897,
  +                               -0.0008052, 0.001612, 0.000664,
  +                               -0.0001897, 0.000664, 0.0005485),
  +                             3L, 3L, dimnames = dns),
  +     stderror.dpq = c(0.02443, 0.04015, 0.02342),
  +     correlation.dpq = matrix(c(1, -0.821, -0.3316,
  +                                -0.821, 1, 0.7061,
  +                                -0.3316, 0.7061, 1), 3),
  +     hessian.dpq = matrix(c(-8252, -5875, 4258,
  +                            -5875, -5420, 4529,
  +                             4258,  4529, -5834),
  +                             3L, 3L, dimnames = dns))
  > stopifnot( all.equal(fd1u[fdCOVcomp], fd1uL, tolerance = 2e-4) )
  > 
  > ## 2)
  > 
  > x2 <-  fracdiff.sim( 2048, ar = .8, ma = -.4, d = .3, n.start=0, allow.0 = TRUE)
  > ## -> NA's and problems
  > fd2 <- fracdiff(x2$series, nar = length(x2$ar), nma = length(x2$ma))
  > sfd2 <- summary(fd2)
  > ss2 <- lapply(sfd2[setdiff(names(sfd2), c("residuals", "fitted"))],
  +               function(.) if(is.numeric(.)) signif(., digits = 7) else .)
  > ss2$coefficients <- ss2$coefficients[, -4] # drop p values
  > ss2S <- list(
  +     log.likelihood = -2924.262, n = 2048,
  +     msg = c(fracdf = "ok", fdcov = "ok"),
  +     covariance.dpq = matrix(c(0.0004182859, -0.0007078449, -6.753008e-05,
  +                              -0.0007078449,  0.001712827,  0.0002692938,
  +                              -6.753008e-05,  0.0002692938, 0.0002572701), 3L,
  +                             dimnames = dns),
  +     fnormMin = 45.62935, sigma = 1.008768,
  +     correlation.dpq = matrix(c(1, -0.8362667, -0.2058572,
  +                                -0.8362667,  1, 0.405672,
  +                                -0.2058572, 0.405672,   1), 3, dimnames = dns),
  +     h = 3.082264e-05, d.tol = 0.0001220703, M = 100,
  +     hessian.dpq = matrix(c(-8557.83, -3810.55,  1742.32,
  +                            -3810.55, -2395.564, 1507.303,
  +                            1742.32, 1507.303, -5007.377), 3, dimnames = dns),
  +     length.w = 10254,
  +     call = quote(
  +         fracdiff(x = x2$series, nar = length(x2$ar), nma = length(x2$ma))),
  +     coefficients = matrix(c(0.3374173,  0.7709664, -0.3810478,
  +                             0.02045204, 0.04138631, 0.01603964,
  +                             16.49798,  18.62854,  -23.75663),
  +                           3, 3, dimnames = dimnames(ss2$coefficients)),
  +     df = 4, aic = 5856.524, symbolic.cor = FALSE)
  > ##
  > if(doExtras)
  +     print(all.equal(ss2S, ss2, tol = 0)) # 0.0001273 (32b Win); TRUE (64b F30, gcc)
  > stopifnot(all.equal(ss2S, ss2, tol = 4e-4))
  > 
  > fd2. <- fracdiff.var(x2$series, fd2, h = fd2$h / 2)
  > sfd2. <-         sapply(fd2.[fdCOVcomp], signif, digits = 4)
  > sfd2S <- ## dput(sapply(fd2.[fdCOVcomp], signif, digits = 5))
  +     list(h = 1.5411e-05,
  +          covariance.dpq = matrix(c( 5.4726e-05,-9.261e-05, -8.8353e-06,
  +                                    -9.261e-05,  0.0006717,  0.00016997,
  +                                    -8.8353e-06, 0.00016997, 0.00024779), 3, dimnames=dns),
  +          stderror.dpq = c(0.0073977, 0.025917, 0.015741),
  +          correlation.dpq = matrix(c(1, -0.48303, -0.075871,
  +                                     -0.48303, 1, 0.41661,
  +                                     -0.075871, 0.41661, 1), 3),
  +          hessian.dpq = matrix(c(-24440,  -3810.6, 1742.3,
  +                                 -3810.6, -2395.6, 1507.3,
  +                                  1742.3,  1507.3,-5007.4), 3, dimnames=dns))
  > ##
  > if(doExtras)
  +     print(all.equal(sfd2S, sfd2., tol = 1e-6, countEQ=TRUE)) # 8.7655e-5
  > stopifnot(all.equal(sfd2S, sfd2., tol = 2e-4, countEQ=TRUE))
  > 
  > fd2u <- fracdiff.var(x2$series, fd2, h = fd2$h * 8)#-> warning, unable .. corr...
  Warning message:
  In fracdiff.var(x2$series, fd2, h = fd2$h * 8) :
    unable to compute correlation matrix
  > sd2u <- sapply(fd2u[fdCOVcomp], signif, digits = 4)
  > sd2uS <- list(  ## dput(sapply(sd2u[fdCOVcomp], signif, digits = 5))
  +     h = 0.0002466,
  +     covariance.dpq = matrix(c(-0.0003545, 6e-04, 5.724e-05,
  +                               6e-04, -0.0005003, 5.816e-05,
  +                               5.724e-05, 5.816e-05, 0.0002371), 3, dimnames=dns),
  +     stderror.dpq = c(0, 0, 0.0154),
  +     correlation.dpq = matrix(0, 3,3),
  +     hessian.dpq = matrix(c(-3347, -3811, 1742,
  +                            -3811, -2396, 1507,
  +                             1742,  1507,-5007), 3, dimnames=dns))
  > ##
  > if(doExtras)
  +     print(all.equal(sd2uS, sd2u, tol = 1e-8, countEQ=TRUE))# 0.000103 (32b Win); T.(64b F30)
  > stopifnot(all.equal(sd2uS, sd2u, tol = 4e-4, countEQ=TRUE))
  Error: sd2uS and sd2u are not equal:
    Component "hessian.dpq": Mean relative difference: 0.00041736
  Execution halted
** running tests for arch 'x64' ... [9s] OK
  Running 'Valderio-ex.R' [1s]
  Comparing 'Valderio-ex.Rout' to 'Valderio-ex.Rout.save' ... OK
  Running 'ex-Vinod.R' [0s]
  Running 'ex.R' [1s]
  Comparing 'ex.Rout' to 'ex.Rout.save' ... OK
  Running 'sim-2.R' [1s]
  Running 'sim-ex.R' [6s]
  Comparing 'sim-ex.Rout' to 'sim-ex.Rout.save' ... OK
* checking PDF version of manual ... OK
* DONE
Status: 1 ERROR, 1 WARNING