Last updated on 2024-09-01 01:48:52 CEST.
Package | NOTE | OK |
---|---|---|
ISwR | 10 | 3 |
Current CRAN status: NOTE: 10, OK: 3
Version: 2.0-8
Check: Rd files
Result: NOTE
checkRd: (-1) secretin.Rd:17: Lost braces
17 | {\code{a}: 1st sample};
| ^
checkRd: (-1) secretin.Rd:18: Lost braces
18 | {\code{b}: 2nd sample}.}
| ^
checkRd: (-1) secretin.Rd:20: Lost braces
20 | {\code{20+}: 20 minutes or longer since injection};
| ^
checkRd: (-1) secretin.Rd:21: Lost braces
21 | {\code{pre}: before injection.}}
| ^
checkRd: (-1) secretin.Rd:23: Lost braces
23 | {\code{20}: 20 minutes since injection};
| ^
checkRd: (-1) secretin.Rd:24: Lost braces
24 | {\code{30+}: 30 minutes or longer since injection};
| ^
checkRd: (-1) secretin.Rd:25: Lost braces
25 | {\code{pre}: before injection. }}
| ^
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
Version: 2.0-8
Check: tests
Result: NOTE
Running ‘allexercises.R’ [8s/25s]
Comparing ‘allexercises.Rout’ to ‘allexercises.Rout.save’ ...192c192
< In wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...) :
---
> In wilcox.test.default(x = c(4.62, 5.29, 5.52, 3.71, 4.02, 5.09, :
224c224
< alternative hypothesis: true mean difference is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
228c228
< mean difference
---
> mean of the differences
1607a1608,1611
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.8492 -0.7536 -0.4838 0.8809 2.5796
>
1633a1638,1641
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.00075 -0.36457 -0.09559 0.57964 1.68281
>
1658a1667,1670
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.9886 -0.4001 -0.2386 0.5503 1.8189
>
1733a1746,1749
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.8298 -0.6412 -0.1189 0.6440 1.7503
>
1806a1823,1826
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.59247 -0.04329 0.00000 0.00063 2.60152
>
1829a1850,1853
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.5641 -0.0247 0.0000 0.0000 2.5668
>
2012a2037,2044
> Deviance Residuals:
> 1 2 3 4 5 6 7 8
> -0.49634 1.16817 0.32723 0.40686 -1.09690 -0.22273 0.16765 -0.30402
> 9 10 11 12 13 14 15 16
> -0.09277 -0.12546 0.37096 0.08185 0.34354 -0.90739 -0.23107 -0.28244
> 17 18 19 20 21 22 23 24
> 0.77919 0.15943 -0.15340 0.30384 0.09596 0.13145 -0.41848 -0.08840
>
2073a2106,2109
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.4288 -0.7090 -0.5282 -0.3361 3.4559
Running ‘allscripts.R’ [7s/18s]
Comparing ‘allscripts.Rout’ to ‘allscripts.Rout.save’ ...487c487
< [1] 190
---
> [1] 185
982c982
< alternative hypothesis: true difference in means between group lean and group obese is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
995c995
< alternative hypothesis: true difference in means between group lean and group obese is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
1024c1024
< In wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...) :
---
> In wilcox.test.default(x = c(7.53, 7.48, 8.08, 8.09, 10.15, 8.4, :
1049c1049
< alternative hypothesis: true mean difference is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
1053c1053
< mean difference
---
> mean of the differences
2749,2751c2749,2751
< gr 1 206698 206698 NaN NaN
< factor(gr) 4 17405 4351 NaN NaN
< Residuals 0 0 NaN
---
> gr 1 206698 206698
> factor(gr) 4 17405 4351
> Residuals 0 0
3004c3004
< alternative hypothesis: true difference in means between group Yes and group No is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
3141a3142,3147
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.04344 0.54145 -0.25476 -0.80051 0.19759 -0.46602
> 7 8
> -0.21262 0.56231
>
3164a3171,3176
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.04344 0.54145 -0.25476 -0.80051 0.19759 -0.46602
> 7 8
> -0.21262 0.56231
>
3187a3200,3205
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.01247 0.47756 -0.24050 -0.82050 0.30794 -0.62742
> 7 8
> -0.14449 0.45770
>
3279a3298,3301
> Deviance Residuals:
> <4 4 4.5 5 5.5 6+
> -0.18531 0.00877 -0.32760 0.34087 1.04313 -0.66215
>
3305c3327
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3307,3309c3329
< shoe.score 1 7.5597 4 1.7845 0.005969 **
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> shoe.score 1 7.5597 4 1.7845
3369a3390,3393
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.32759 -0.18998 0.01253 0.12132 2.45922
>
3389a3414,3417
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.56180 -0.12461 0.02475 0.08055 2.86120
>
3487a3516,3519
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.45697 -0.15434 0.00835 0.09505 2.59033
>
3516c3548
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3518,3521c3550,3551
< age 1 518.73 517 200.66 < 2e-16 ***
< age.gr 3 8.06 514 192.61 0.04483 *
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> age 1 518.73 517 200.66
> age.gr 3 8.06 514 192.61
3534c3564
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3536,3541c3566,3569
< age 1 518.73 517 200.66 < 2.2e-16 ***
< I(age^2) 1 0.05 516 200.61 0.819906
< I(age^3) 1 8.82 515 191.80 0.002984 **
< age.gr 3 3.34 512 188.46 0.342745
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> age 1 518.73 517 200.66
> I(age^2) 1 0.05 516 200.61
> I(age^3) 1 8.82 515 191.80
> age.gr 3 3.34 512 188.46
3592c3620
< [1,] 205 57 NA NA NA
---
> 205 57 NA NA NA
3733a3762,3765
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.63573 -0.67296 -0.03436 0.37258 1.85267
>
3799a3832,3835
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.64704 -0.62400 0.02301 0.36721 1.84308
>
3947a3984,3987
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.6758 -0.3159 -0.1821 -0.0918 4.1972
>
4009a4050,4053
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.4215 -0.3452 -0.2490 -0.1429 3.9398
>
4076a4121,4124
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.8113 -0.3172 -0.2168 -0.1196 4.1466
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 2.0-8
Check: tests
Result: NOTE
Running ‘allexercises.R’
Comparing ‘allexercises.Rout’ to ‘allexercises.Rout.save’ ...192c192
< In wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...) :
---
> In wilcox.test.default(x = c(4.62, 5.29, 5.52, 3.71, 4.02, 5.09, :
224c224
< alternative hypothesis: true mean difference is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
228c228
< mean difference
---
> mean of the differences
1607a1608,1611
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.8492 -0.7536 -0.4838 0.8809 2.5796
>
1633a1638,1641
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.00075 -0.36457 -0.09559 0.57964 1.68281
>
1658a1667,1670
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.9886 -0.4001 -0.2386 0.5503 1.8189
>
1733a1746,1749
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.8298 -0.6412 -0.1189 0.6440 1.7503
>
1806a1823,1826
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.59247 -0.04329 0.00000 0.00063 2.60152
>
1829a1850,1853
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.5641 -0.0247 0.0000 0.0000 2.5668
>
2012a2037,2044
> Deviance Residuals:
> 1 2 3 4 5 6 7 8
> -0.49634 1.16817 0.32723 0.40686 -1.09690 -0.22273 0.16765 -0.30402
> 9 10 11 12 13 14 15 16
> -0.09277 -0.12546 0.37096 0.08185 0.34354 -0.90739 -0.23107 -0.28244
> 17 18 19 20 21 22 23 24
> 0.77919 0.15943 -0.15340 0.30384 0.09596 0.13145 -0.41848 -0.08840
>
2073a2106,2109
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.4288 -0.7090 -0.5282 -0.3361 3.4559
Running ‘allscripts.R’
Comparing ‘allscripts.Rout’ to ‘allscripts.Rout.save’ ...487c487
< [1] 190
---
> [1] 185
982c982
< alternative hypothesis: true difference in means between group lean and group obese is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
995c995
< alternative hypothesis: true difference in means between group lean and group obese is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
1024c1024
< In wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...) :
---
> In wilcox.test.default(x = c(7.53, 7.48, 8.08, 8.09, 10.15, 8.4, :
1049c1049
< alternative hypothesis: true mean difference is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
1053c1053
< mean difference
---
> mean of the differences
2749,2751c2749,2751
< gr 1 206698 206698 NaN NaN
< factor(gr) 4 17405 4351 NaN NaN
< Residuals 0 0 NaN
---
> gr 1 206698 206698
> factor(gr) 4 17405 4351
> Residuals 0 0
3004c3004
< alternative hypothesis: true difference in means between group Yes and group No is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
3141a3142,3147
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.04344 0.54145 -0.25476 -0.80051 0.19759 -0.46602
> 7 8
> -0.21262 0.56231
>
3164a3171,3176
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.04344 0.54145 -0.25476 -0.80051 0.19759 -0.46602
> 7 8
> -0.21262 0.56231
>
3187a3200,3205
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.01247 0.47756 -0.24050 -0.82050 0.30794 -0.62742
> 7 8
> -0.14449 0.45770
>
3279a3298,3301
> Deviance Residuals:
> <4 4 4.5 5 5.5 6+
> -0.18531 0.00877 -0.32760 0.34087 1.04313 -0.66215
>
3305c3327
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3307,3309c3329
< shoe.score 1 7.5597 4 1.7845 0.005969 **
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> shoe.score 1 7.5597 4 1.7845
3369a3390,3393
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.32759 -0.18998 0.01253 0.12132 2.45922
>
3389a3414,3417
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.56180 -0.12461 0.02475 0.08055 2.86120
>
3487a3516,3519
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.45697 -0.15434 0.00835 0.09505 2.59033
>
3516c3548
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3518,3521c3550,3551
< age 1 518.73 517 200.66 < 2e-16 ***
< age.gr 3 8.06 514 192.61 0.04483 *
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> age 1 518.73 517 200.66
> age.gr 3 8.06 514 192.61
3534c3564
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3536,3541c3566,3569
< age 1 518.73 517 200.66 < 2.2e-16 ***
< I(age^2) 1 0.05 516 200.61 0.819906
< I(age^3) 1 8.82 515 191.80 0.002984 **
< age.gr 3 3.34 512 188.46 0.342745
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> age 1 518.73 517 200.66
> I(age^2) 1 0.05 516 200.61
> I(age^3) 1 8.82 515 191.80
> age.gr 3 3.34 512 188.46
3592c3620
< [1,] 205 57 NA NA NA
---
> 205 57 NA NA NA
3733a3762,3765
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.63573 -0.67296 -0.03436 0.37258 1.85267
>
3799a3832,3835
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.64704 -0.62400 0.02301 0.36721 1.84308
>
3947a3984,3987
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.6758 -0.3159 -0.1821 -0.0918 4.1972
>
4009a4050,4053
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.4215 -0.3452 -0.2490 -0.1429 3.9398
>
4076a4121,4124
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.8113 -0.3172 -0.2168 -0.1196 4.1466
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 2.0-8
Check: tests
Result: NOTE
Running 'allexercises.R' [5s]
Comparing 'allexercises.Rout' to 'allexercises.Rout.save' ...192c192
< In wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...) :
---
> In wilcox.test.default(x = c(4.62, 5.29, 5.52, 3.71, 4.02, 5.09, :
224c224
< alternative hypothesis: true mean difference is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
228c228
< mean difference
---
> mean of the differences
724c724
< 60-64:4 Hist.ctr. :6 Median :104.0 Median : 169261
---
> 60-64:4 Hist.ctr. :6 Median :104.0 Median : 169260
1607a1608,1611
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.8492 -0.7536 -0.4838 0.8809 2.5796
>
1633a1638,1641
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.00075 -0.36457 -0.09559 0.57964 1.68281
>
1658a1667,1670
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.9886 -0.4001 -0.2386 0.5503 1.8189
>
1733a1746,1749
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.8298 -0.6412 -0.1189 0.6440 1.7503
>
1806a1823,1826
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.59247 -0.04329 0.00000 0.00063 2.60152
>
1829a1850,1853
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.5641 -0.0247 0.0000 0.0000 2.5668
>
2012a2037,2044
> Deviance Residuals:
> 1 2 3 4 5 6 7 8
> -0.49634 1.16817 0.32723 0.40686 -1.09690 -0.22273 0.16765 -0.30402
> 9 10 11 12 13 14 15 16
> -0.09277 -0.12546 0.37096 0.08185 0.34354 -0.90739 -0.23107 -0.28244
> 17 18 19 20 21 22 23 24
> 0.77919 0.15943 -0.15340 0.30384 0.09596 0.13145 -0.41848 -0.08840
>
2073a2106,2109
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.4288 -0.7090 -0.5282 -0.3361 3.4559
Running 'allscripts.R' [4s]
Comparing 'allscripts.Rout' to 'allscripts.Rout.save' ...487c487
< [1] 191
---
> [1] 185
982c982
< alternative hypothesis: true difference in means between group lean and group obese is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
995c995
< alternative hypothesis: true difference in means between group lean and group obese is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
1024c1024
< In wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...) :
---
> In wilcox.test.default(x = c(7.53, 7.48, 8.08, 8.09, 10.15, 8.4, :
1049c1049
< alternative hypothesis: true mean difference is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
1053c1053
< mean difference
---
> mean of the differences
2749,2751c2749,2751
< gr 1 206698 206698 NaN NaN
< factor(gr) 4 17405 4351 NaN NaN
< Residuals 0 0 NaN
---
> gr 1 206698 206698
> factor(gr) 4 17405 4351
> Residuals 0 0
3004c3004
< alternative hypothesis: true difference in means between group Yes and group No is not equal to 0
---
> alternative hypothesis: true difference in means is not equal to 0
3141a3142,3147
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.04344 0.54145 -0.25476 -0.80051 0.19759 -0.46602
> 7 8
> -0.21262 0.56231
>
3164a3171,3176
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.04344 0.54145 -0.25476 -0.80051 0.19759 -0.46602
> 7 8
> -0.21262 0.56231
>
3187a3200,3205
> Deviance Residuals:
> 1 2 3 4 5 6
> -0.01247 0.47756 -0.24050 -0.82050 0.30794 -0.62742
> 7 8
> -0.14449 0.45770
>
3279a3298,3301
> Deviance Residuals:
> <4 4 4.5 5 5.5 6+
> -0.18531 0.00877 -0.32760 0.34087 1.04313 -0.66215
>
3305c3327
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3307,3309c3329
< shoe.score 1 7.5597 4 1.7845 0.005969 **
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> shoe.score 1 7.5597 4 1.7845
3369a3390,3393
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.32759 -0.18998 0.01253 0.12132 2.45922
>
3389a3414,3417
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.56180 -0.12461 0.02475 0.08055 2.86120
>
3487a3516,3519
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.45697 -0.15434 0.00835 0.09505 2.59033
>
3516c3548
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3518,3521c3550,3551
< age 1 518.73 517 200.66 < 2e-16 ***
< age.gr 3 8.06 514 192.61 0.04483 *
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> age 1 518.73 517 200.66
> age.gr 3 8.06 514 192.61
3534c3564
< Df Deviance Resid. Df Resid. Dev Pr(>Chi)
---
> Df Deviance Resid. Df Resid. Dev
3536,3541c3566,3569
< age 1 518.73 517 200.66 < 2.2e-16 ***
< I(age^2) 1 0.05 516 200.61 0.819906
< I(age^3) 1 8.82 515 191.80 0.002984 **
< age.gr 3 3.34 512 188.46 0.342745
< ---
< Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
---
> age 1 518.73 517 200.66
> I(age^2) 1 0.05 516 200.61
> I(age^3) 1 8.82 515 191.80
> age.gr 3 3.34 512 188.46
3592c3620
< [1,] 205 57 NA NA NA
---
> 205 57 NA NA NA
3733a3762,3765
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.63573 -0.67296 -0.03436 0.37258 1.85267
>
3799a3832,3835
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.64704 -0.62400 0.02301 0.36721 1.84308
>
3947a3984,3987
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.6758 -0.3159 -0.1821 -0.0918 4.1972
>
4009a4050,4053
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.4215 -0.3452 -0.2490 -0.1429 3.9398
>
4076a4121,4124
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -0.8113 -0.3172 -0.2168 -0.1196 4.1466
Flavor: r-devel-windows-x86_64