Last updated on 2026-08-04 04:51:20 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.4 | 2.35 | 28.66 | 31.01 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 1.4 | 2.04 | 22.78 | 24.82 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 1.4 | 46.55 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 1.4 | 21.61 | NOTE | |||
| r-devel-windows-x86_64 | 1.4 | 4.00 | 52.00 | 56.00 | NOTE | |
| r-patched-linux-x86_64 | 1.4 | 2.29 | 26.67 | 28.96 | NOTE | |
| r-release-linux-x86_64 | 1.4 | 2.45 | 26.80 | 29.25 | NOTE | |
| r-release-macos-arm64 | 1.4 | 1.00 | 10.00 | 11.00 | NOTE | |
| r-release-macos-x86_64 | 1.4 | 2.00 | 36.00 | 38.00 | NOTE | |
| r-release-windows-x86_64 | 1.4 | 5.00 | 54.00 | 59.00 | NOTE | |
| r-oldrel-macos-arm64 | 1.4 | NOTE | ||||
| r-oldrel-macos-x86_64 | 1.4 | 2.00 | 30.00 | 32.00 | NOTE | |
| r-oldrel-windows-x86_64 | 1.4 | 6.00 | 53.00 | 59.00 | NOTE |
Version: 1.4
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Przemyslaw Biecek <przemyslaw.biecek@gmail.com>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Przemyslaw",
family = "Biecek",
role = c("aut", "cre"),
email = "przemyslaw.biecek@gmail.com",
comment = "R code"),
person(given = "Teresa",
family = "Ledwina",
role = "aut",
comment = "support,\n descriptions"))
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.4
Check: R code for possible problems
Result: NOTE
Found calls to structure() using deprecated special names:
ddst/R/ddst.exp.test.R (.Dim: 20)
ddst/R/ddst.extr.test.R (.Dim: 41)
ddst/R/ddst.norm.test.R (.Dim: 40)
ddst/R/zzz.R (.Dim: 1, .Dimnames: 1)
'.Dim' should be changed to 'dim'.
'.Dimnames' should be changed to 'dimnames'.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64
Version: 1.4
Check: Rd files
Result: NOTE
checkRd: (-1) ddst-package.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$W_k=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1}[1/sqrt(n) sum_{i=1}^n l(Z_i)]'$},
| ^
checkRd: (-1) ddst-package.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$W_k=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1}[1/sqrt(n) sum_{i=1}^n l(Z_i)]'$},
| ^
checkRd: (-1) ddst-package.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$W_k=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1}[1/sqrt(n) sum_{i=1}^n l(Z_i)]'$},
| ^
checkRd: (-1) ddst-package.Rd:31: Lost braces; missing escapes or markup?
31 | where \emph{$l(Z_i)$}, i=1,...,n, is \emph{k}-dimensional (row) score vector, the symbol \emph{'} denotes transposition while \emph{$I=Cov_{theta_0}[l(Z_1)]'[l(Z_1)]$}. Following Neyman's idea of modelling underlying distributions one gets \emph{$l(Z_i)=(phi_1(F(Z_i)),...,phi_k(F(Z_i)))$} and \emph{I} being the identity matrix, where \emph{$phi_j$}'s, j >= 1, are zero mean orthonormal functions on [0,1], while \emph{F} is the completely specified null distribution function.
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:36: Lost braces; missing escapes or markup?
36 | where \emph{$tilde gamma$} is an appropriate estimator of \emph{$gamma$} while \emph{$I^*(gamma)=Cov_{theta_0}[l^*(Z_1;gamma)]'[l^*(Z_1;gamma)]$}. More details can be found in Janic and Ledwina (2008), Kallenberg and Ledwina (1997 a,b) as well as Inglot and Ledwina (2006 a,b).
| ^
checkRd: (-1) ddst-package.Rd:40: Lost braces
40 | \emph{$T = min{1 <= k <= d: W_k-pi(k,n,c) >= W_j-pi(j,n,c), j=1,...,d}$}
| ^
checkRd: (-1) ddst-package.Rd:45: Lost braces
45 | $T^* = min{1 <= k <= d: W_k^*(tilde gamma)-pi^*(k,n,c) >= W_j^*(tilde gamma)-pi^*(j,n,c), j=1,...,d}$}.
| ^
checkRd: (-1) ddst-package.Rd:49: Lost braces
49 | \emph{$pi(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k| <= sqrt(c log(n)), 2j, if max{1 <= k <= d}|Y_k|>sqrt(c log(n)). }$}
| ^
checkRd: (-1) ddst-package.Rd:49: Lost braces
49 | \emph{$pi(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k| <= sqrt(c log(n)), 2j, if max{1 <= k <= d}|Y_k|>sqrt(c log(n)). }$}
| ^
checkRd: (-1) ddst-package.Rd:49: Lost braces
49 | \emph{$pi(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k| <= sqrt(c log(n)), 2j, if max{1 <= k <= d}|Y_k|>sqrt(c log(n)). }$}
| ^
checkRd: (-1) ddst-package.Rd:54: Lost braces
54 | $pi^*(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k^*| <= sqrt(c log(n)),2j if max(1 <= k <= d)|Y_k^*| > sqrt(c log(n))}$}.
| ^
checkRd: (-1) ddst-package.Rd:54: Lost braces
54 | $pi^*(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k^*| <= sqrt(c log(n)),2j if max(1 <= k <= d)|Y_k^*| > sqrt(c log(n))}$}.
| ^
checkRd: (-1) ddst-package.Rd:58: Lost braces; missing escapes or markup?
58 | \emph{$(Y_1,...,Y_k)=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1/2}$}
| ^
checkRd: (-1) ddst-package.Rd:58: Lost braces; missing escapes or markup?
58 | \emph{$(Y_1,...,Y_k)=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1/2}$}
| ^
checkRd: (-1) ddst-package.Rd:62: Lost braces; missing escapes or markup?
62 | \emph{$(Y_1^*,...,Y_k^*)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i; tilde gamma)][I^*(tilde gamma)]^{-1/2}$}.
| ^
checkRd: (-1) ddst-package.Rd:62: Lost braces; missing escapes or markup?
62 | \emph{$(Y_1^*,...,Y_k^*)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i; tilde gamma)][I^*(tilde gamma)]^{-1/2}$}.
| ^
checkRd: (-1) ddst-package.Rd:65: Lost braces; missing escapes or markup?
65 | and \emph{$W_{T^*} = W_{T^*}(tilde gamma)$}, respectively. For details see Inglot and Ledwina (2006 a,b,c).
| ^
checkRd: (-1) ddst-package.Rd:65: Lost braces; missing escapes or markup?
65 | and \emph{$W_{T^*} = W_{T^*}(tilde gamma)$}, respectively. For details see Inglot and Ledwina (2006 a,b,c).
| ^
checkRd: (-1) ddst-package.Rd:67: Lost braces; missing escapes or markup?
67 | The choice of \emph{c} in \emph{T} and \emph{$T^*$} is decisive to finite sample behaviour of the selection rules and pertaining statistics \emph{$W_T$} and \emph{$W_{T^*}(tilde gamma)$}. In particular, under large \emph{c}'s the rules behave similarly as Schwarz's (1978) BIC while for \emph{c=0} they mimic Akaike's (1973) AIC. For moderate sample sizes, values \emph{c in (2,2.5)} guarantee, under `smooth' departures, only slightly smaller power as in case BIC were used and simultaneously give much higher power than BIC under multimodal alternatives. In genral, large \emph{c's} are recommended if changes in location, scale, skewness and kurtosis are in principle aimed to be detected. For evidence and discussion see Inglot and Ledwina (2006 c).
| ^
checkRd: (-1) ddst-package.Rd:69: Lost braces; missing escapes or markup?
69 | It \emph{c>0} then the limiting null distribution of \emph{$W_T$} and \emph{$W_{T^*}(tilde gamma)$} is central chi-squared with one degree of freedom. In our implementation, for given \emph{n}, both critical values and \emph{p}-values are computed by MC method.
| ^
checkRd: (-1) ddst-package.Rd:71: Lost braces; missing escapes or markup?
71 | Empirical distributions of \emph{T} and \emph{$T^*$} as well as \emph{$W_T$} and \emph{$W_{T^*}(tilde gamma)$} are not essentially influenced by the choice of reasonably large \emph{d}'s, provided that sample size is at least moderate.
| ^
checkRd: (-1) ddst.exp.test.Rd:27: Lost braces; missing escapes or markup?
27 | Modelling alternatives similarly as in Kallenberg and Ledwina (1997 a,b), e.g., and estimating \emph{$gamma$} by \emph{$tilde gamma= 1/n sum_{i=1}^n Z_i$} yields the efficient score
| ^
checkRd: (-1) ddst.exp.test.Rd:30: Lost braces; missing escapes or markup?
30 | The matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and computed in a numerical way in case of cosine basis. In the implementation the default value of \emph{c} in \emph{$T^*$} is set to be 100.
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:33: Lost braces; missing escapes or markup?
33 | The related matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and numerical methods for cosine functions. In the implementation the default value of \emph{c} in \emph{$T^*$} was fixed to be 100. Hence, \emph{$T^*$} is Schwarz-type model selection rule. The resulting data driven test statistic for extreme value distribution is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.extr.test.Rd:33: Lost braces; missing escapes or markup?
33 | The related matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and numerical methods for cosine functions. In the implementation the default value of \emph{c} in \emph{$T^*$} was fixed to be 100. Hence, \emph{$T^*$} is Schwarz-type model selection rule. The resulting data driven test statistic for extreme value distribution is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.extr.test.Rd:33: Lost braces; missing escapes or markup?
33 | The related matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and numerical methods for cosine functions. In the implementation the default value of \emph{c} in \emph{$T^*$} was fixed to be 100. Hence, \emph{$T^*$} is Schwarz-type model selection rule. The resulting data driven test statistic for extreme value distribution is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.norm.test.Rd:30: Lost braces; missing escapes or markup?
30 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=1/n sum_{i=1}^n Z_i$} and
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:32: Lost braces; missing escapes or markup?
32 | while \emph{$Z_{n:1}<= ... <= Z_{n:n}$} are ordered values of \emph{$Z_1, ..., Z_n$} and \emph{$H_i= phi^{-1}((i-3/8)(n+1/4))$}, cf. Chen and Shapiro (1995).
| ^
checkRd: (-1) ddst.norm.test.Rd:32: Lost braces; missing escapes or markup?
32 | while \emph{$Z_{n:1}<= ... <= Z_{n:n}$} are ordered values of \emph{$Z_1, ..., Z_n$} and \emph{$H_i= phi^{-1}((i-3/8)(n+1/4))$}, cf. Chen and Shapiro (1995).
| ^
checkRd: (-1) ddst.norm.test.Rd:32: Lost braces; missing escapes or markup?
32 | while \emph{$Z_{n:1}<= ... <= Z_{n:n}$} are ordered values of \emph{$Z_1, ..., Z_n$} and \emph{$H_i= phi^{-1}((i-3/8)(n+1/4))$}, cf. Chen and Shapiro (1995).
| ^
checkRd: (-1) ddst.norm.test.Rd:35: Lost braces; missing escapes or markup?
35 | The pertaining matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and is computed in a numerical way in case of cosine basis. In the implementation of \emph{$T^*$} the default value of \emph{c} is set to be 100. Therefore, in practice, \emph{$T^*$} is Schwarz-type criterion. See Inglot and Ledwina (2006) as well as Janic and Ledwina (2008) for comments. The resulting data driven test statistic for normality is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.norm.test.Rd:35: Lost braces; missing escapes or markup?
35 | The pertaining matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and is computed in a numerical way in case of cosine basis. In the implementation of \emph{$T^*$} the default value of \emph{c} is set to be 100. Therefore, in practice, \emph{$T^*$} is Schwarz-type criterion. See Inglot and Ledwina (2006) as well as Janic and Ledwina (2008) for comments. The resulting data driven test statistic for normality is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.norm.test.Rd:35: Lost braces; missing escapes or markup?
35 | The pertaining matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and is computed in a numerical way in case of cosine basis. In the implementation of \emph{$T^*$} the default value of \emph{c} is set to be 100. Therefore, in practice, \emph{$T^*$} is Schwarz-type criterion. See Inglot and Ledwina (2006) as well as Janic and Ledwina (2008) for comments. The resulting data driven test statistic for normality is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.uniform.test.Rd:25: Lost braces; missing escapes or markup?
25 | $W_k=[1/sqrt(n) sum_{j=1}^k sum_{i=1}^n phi_j(Z_i)]^2$},
| ^
checkRd: (-1) ddst.uniform.test.Rd:25: Lost braces; missing escapes or markup?
25 | $W_k=[1/sqrt(n) sum_{j=1}^k sum_{i=1}^n phi_j(Z_i)]^2$},
| ^
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 1.4
Check: for new files in some other directories
Result: NOTE
Found the following files/directories:
‘~/tmp/scratch/Rtmp0vFmdq’ ‘~/tmp/scratch/Rtmp11mot3’
‘~/tmp/scratch/Rtmp2ZEDjW’ ‘~/tmp/scratch/Rtmp3M7hok’
‘~/tmp/scratch/Rtmp3e6bqc’ ‘~/tmp/scratch/Rtmp3jezta’
‘~/tmp/scratch/Rtmp4Xuvus’ ‘~/tmp/scratch/Rtmp4yMdGc’
‘~/tmp/scratch/Rtmp5FkLGk’ ‘~/tmp/scratch/Rtmp5IaHzk’
‘~/tmp/scratch/Rtmp5eG0k4’ ‘~/tmp/scratch/Rtmp685PXT’
‘~/tmp/scratch/Rtmp6mbwZo’ ‘~/tmp/scratch/Rtmp7tjRvl’
‘~/tmp/scratch/Rtmp7uD3mx’ ‘~/tmp/scratch/Rtmp87KS4H’
‘~/tmp/scratch/RtmpB33giY’ ‘~/tmp/scratch/RtmpC3G1uh’
‘~/tmp/scratch/RtmpCGUOei’ ‘~/tmp/scratch/RtmpCUrZko’
‘~/tmp/scratch/RtmpCwK5mF’ ‘~/tmp/scratch/RtmpDGClXb’
‘~/tmp/scratch/RtmpDNSleu’ ‘~/tmp/scratch/RtmpDTwhiy’
‘~/tmp/scratch/RtmpDXLNM0’ ‘~/tmp/scratch/RtmpDsBwBU’
‘~/tmp/scratch/RtmpDv4rTO’ ‘~/tmp/scratch/RtmpDw4vLT’
‘~/tmp/scratch/RtmpESYds7’ ‘~/tmp/scratch/RtmpEaMGfN’
‘~/tmp/scratch/RtmpEqt5q0’ ‘~/tmp/scratch/RtmpEu53Qn’
‘~/tmp/scratch/RtmpF8O8Ra’ ‘~/tmp/scratch/RtmpFBd9gp’
‘~/tmp/scratch/RtmpGqxO34’ ‘~/tmp/scratch/RtmpHecF6d’
‘~/tmp/scratch/RtmpIlXbXl’ ‘~/tmp/scratch/RtmpJk4lVP’
‘~/tmp/scratch/RtmpKHXh5u’ ‘~/tmp/scratch/RtmpKQULMY’
‘~/tmp/scratch/RtmpKtcNYX’ ‘~/tmp/scratch/RtmpKweeIx’
‘~/tmp/scratch/RtmpLDJUe2’ ‘~/tmp/scratch/RtmpLYcM7e’
‘~/tmp/scratch/RtmpLfgubO’ ‘~/tmp/scratch/RtmpMoxjb5’
‘~/tmp/scratch/RtmpMxAw41’ ‘~/tmp/scratch/RtmpObi0W4’
‘~/tmp/scratch/RtmpP2Zj0B’ ‘~/tmp/scratch/RtmpPWf9HF’
‘~/tmp/scratch/RtmpPnTRiX’ ‘~/tmp/scratch/RtmpRQ5Xwk’
‘~/tmp/scratch/RtmpRlIf9n’ ‘~/tmp/scratch/RtmpTM2iGY’
‘~/tmp/scratch/RtmpTnkhbS’ ‘~/tmp/scratch/RtmpUKRf5F’
‘~/tmp/scratch/RtmpUNoOPJ’ ‘~/tmp/scratch/RtmpUoshlc’
‘~/tmp/scratch/RtmpUrGCYO’ ‘~/tmp/scratch/RtmpVSYrKj’
‘~/tmp/scratch/RtmpW1NjOf’ ‘~/tmp/scratch/RtmpWImuaK’
‘~/tmp/scratch/RtmpWuosK8’ ‘~/tmp/scratch/RtmpZ2Pq2C’
‘~/tmp/scratch/RtmpZ8At1l’ ‘~/tmp/scratch/RtmpaWuVOR’
‘~/tmp/scratch/RtmpdgeJqR’ ‘~/tmp/scratch/RtmpeUKoD5’
‘~/tmp/scratch/RtmpfFtshd’ ‘~/tmp/scratch/Rtmpg0cBi7’
‘~/tmp/scratch/RtmphJ1vTV’ ‘~/tmp/scratch/RtmphaCVuD’
‘~/tmp/scratch/RtmphiES1N’ ‘~/tmp/scratch/RtmphrqcOy’
‘~/tmp/scratch/RtmphvItuJ’ ‘~/tmp/scratch/RtmpiFbQkF’
‘~/tmp/scratch/Rtmpk9OqhY’ ‘~/tmp/scratch/RtmpkMkiVa’
‘~/tmp/scratch/RtmpktdRNM’ ‘~/tmp/scratch/RtmpkyZuW1’
‘~/tmp/scratch/RtmplYvpqe’ ‘~/tmp/scratch/Rtmpli2dKm’
‘~/tmp/scratch/Rtmpmc8i0n’ ‘~/tmp/scratch/RtmpmclIFB’
‘~/tmp/scratch/RtmpmpwEWZ’ ‘~/tmp/scratch/RtmpnGgbG8’
‘~/tmp/scratch/RtmpnphmI0’ ‘~/tmp/scratch/RtmpoEcpX5’
‘~/tmp/scratch/RtmpoJ3JAm’ ‘~/tmp/scratch/Rtmpozv1pb’
‘~/tmp/scratch/RtmpqJnnU3’ ‘~/tmp/scratch/RtmprBfxTf’
‘~/tmp/scratch/RtmptjLyum’ ‘~/tmp/scratch/RtmptqCvMz’
‘~/tmp/scratch/Rtmpu2U38F’ ‘~/tmp/scratch/RtmpuXEaYa’
‘~/tmp/scratch/Rtmpv4ZbOY’ ‘~/tmp/scratch/Rtmpwma7gI’
‘~/tmp/scratch/RtmpwrFKWs’ ‘~/tmp/scratch/RtmpxNZH9v’
‘~/tmp/scratch/RtmpyHdsee’ ‘~/tmp/scratch/RtmpySf0xT’
‘~/tmp/scratch/Rtmpyp2GjZ’ ‘~/tmp/scratch/Rtmpz5mUjt’
‘~/tmp/scratch/RtmpzUsdsv’ ‘~/tmp/scratch/RtmpzkoyDB’
‘~/tmp/scratch/quarto-sessionef440190ea124975’
‘~/tmp/scratch/xvfb-run.0maOtq’ ‘~/tmp/scratch/xvfb-run.1GHsOJ’
‘~/tmp/scratch/xvfb-run.2cUtXi’ ‘~/tmp/scratch/xvfb-run.5pedsB’
‘~/tmp/scratch/xvfb-run.9dDeON’ ‘~/tmp/scratch/xvfb-run.DsvAeB’
‘~/tmp/scratch/xvfb-run.HQDzUp’ ‘~/tmp/scratch/xvfb-run.JnDuYr’
‘~/tmp/scratch/xvfb-run.N2KtiF’ ‘~/tmp/scratch/xvfb-run.OX1aUj’
‘~/tmp/scratch/xvfb-run.YPK7qN’ ‘~/tmp/scratch/xvfb-run.jAI53x’
‘~/tmp/scratch/xvfb-run.jMP4I6’ ‘~/tmp/scratch/xvfb-run.kDexbC’
‘~/tmp/scratch/xvfb-run.lqWadn’ ‘~/tmp/scratch/xvfb-run.nAuXYh’
‘~/tmp/scratch/xvfb-run.r2Wy0Q’ ‘~/tmp/scratch/xvfb-run.rPYxB1’
‘~/tmp/scratch/xvfb-run.rpxGhd’ ‘~/tmp/scratch/xvfb-run.tMgxj4’
‘~/tmp/scratch/xvfb-run.vC3CDA’ ‘~/tmp/scratch/xvfb-run.vL38wv’
‘~/tmp/scratch/xvfb-run.vUfcWb’ ‘~/tmp/scratch/xvfb-run.xDlE5M’
‘~/tmp/scratch/xvfb-run.xEe9Dw’ ‘~/tmp/scratch/xvfb-run.xWq5Yq’
‘~/tmp/scratch/xvfb-run.zh2xdZ’
Flavor: r-devel-linux-x86_64-debian-gcc