Last updated on 2023-03-20 15:57:17 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.47.1 | ERROR | ||||
| r-devel-linux-x86_64-debian-gcc | 1.47.1 | 14.88 | 140.97 | 155.85 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.47.1 | 260.70 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.47.1 | 253.62 | ERROR | |||
| r-devel-windows-x86_64 | 1.47.1 | 104.00 | 215.00 | 319.00 | ERROR | |
| r-patched-linux-x86_64 | 1.47.1 | 20.31 | 181.65 | 201.96 | OK | |
| r-release-linux-x86_64 | 1.47.1 | 18.60 | 172.18 | 190.78 | OK | |
| r-release-macos-arm64 | 1.47.1 | 65.00 | OK | |||
| r-release-macos-x86_64 | 1.47.1 | 99.00 | OK | |||
| r-release-windows-x86_64 | 1.47.1 | 82.00 | 240.00 | 322.00 | OK | |
| r-oldrel-macos-arm64 | 1.46.0 | 69.00 | OK | |||
| r-oldrel-macos-x86_64 | 1.46.0 | 95.00 | OK | |||
| r-oldrel-windows-ix86+x86_64 | 1.46.0 | 34.00 | 209.00 | 243.00 | OK |
Version: 1.47.1
Check: examples
Result: ERROR
Running examples in ‘MuMIn-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: MuMIn-package
> ### Title: Multi-model inference
> ### Aliases: MuMIn-package MuMIn
> ### Keywords: package models
>
> ### ** Examples
>
> ## Don't show:
> oop <-
+ ## End(Don't show)
+ options(na.action = "na.fail") # change the default "na.omit" to prevent models
> # from being fitted to different datasets in
> # case of missing values.
>
> fm1 <- lm(y ~ ., data = Cement)
> ms1 <- dredge(fm1)
Fixed term is "(Intercept)"
>
> # Visualize the model selection table:
> ## Don't show:
> if(require(graphics)) {
+ ## End(Don't show)
+ par(mar = c(3,5,6,4))
+ plot(ms1, labAsExpr = TRUE)
+ ## Don't show:
+ }
> ## End(Don't show)
> model.avg(ms1, subset = delta < 4)
Call:
model.avg(object = ms1, subset = delta < 4)
Component models:
‘12’ ‘124’ ‘123’ ‘14’ ‘134’
Coefficients:
(Intercept) X1 X2 X4 X3
full 64.69313 1.455798 0.5057578 -0.1478697 -0.004302377
subset 64.69313 1.455798 0.6250260 -0.4760071 -0.021531961
>
> confset.95p <- get.models(ms1, cumsum(weight) <= .95)
> avgmod.95p <- model.avg(confset.95p)
> summary(avgmod.95p)
Call:
model.avg(object = confset.95p)
Component model call:
lm(formula = y ~ <4 unique rhs>, data = Cement)
Component models:
df logLik AICc delta weight
12 4 -28.16 69.31 0.00 0.62
124 5 -26.93 72.44 3.13 0.13
123 5 -26.95 72.48 3.16 0.13
14 4 -29.82 72.63 3.32 0.12
Term codes:
X1 X2 X3 X4
1 2 3 4
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 60.48430 17.92604 18.21471 3.321 0.000898 ***
X1 1.49198 0.15745 0.17467 8.542 < 2e-16 ***
X2 0.55106 0.23133 0.23552 2.340 0.019299 *
X4 -0.10354 0.21306 0.21628 0.479 0.632129
X3 0.03204 0.10656 0.11317 0.283 0.777105
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 60.4843 17.9260 18.2147 3.321 0.000898 ***
X1 1.4920 0.1575 0.1747 8.542 < 2e-16 ***
X2 0.6250 0.1203 0.1292 4.839 1.31e-06 ***
X4 -0.4160 0.2289 0.2408 1.728 0.084009 .
X3 0.2500 0.1847 0.2132 1.173 0.240898
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> confint(avgmod.95p)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.47.1
Check: tests
Result: ERROR
Running ‘gam-smooth-match.R’ [4s/5s]
Running ‘gam.R’ [5s/6s]
Running ‘glm.R’ [3s/3s]
Running ‘glm.nb.R’ [4s/5s]
Running ‘misc-tests.R’ [3s/3s]
Running ‘multinom.R’ [3s/4s]
Running ‘nlme.R’ [4s/4s]
Running ‘parallel.R’ [10s/20s]
Running ‘quasibinomial.R’ [3s/4s]
Running ‘rlm.R’ [3s/3s]
Running ‘singularities.R’ [3s/4s]
Running ‘survival.R’ [4s/6s]
Running the tests in ‘tests/glm.R’ failed.
Complete output:
> library("MuMIn")
> options(na.action = "na.fail")
> data(Orthodont, package = "nlme")
>
> fm1 <- lm(distance ~ Sex * age + age * Sex, data = Orthodont)
>
> dispersion <- function(object) {
+ wts <- weights(object)
+ if (is.null(wts))
+ wts <- 1
+ sum((wts * resid(object, type = "working")^2)[wts > 0])/df.residual(object)
+ }
>
> dd <- dredge(fm1, extra = alist(dispersion))
Fixed term is "(Intercept)"
> gm <- get.models(dd, subset = 1:4)
> ma <- model.avg(gm, revised = F)
>
> vcov(ma)
(Intercept) SexFemale age SexFemale:age
(Intercept) 2.1094155 -2.2423049 -0.18448478 0.17510000
SexFemale -2.2423049 5.5038392 0.19656574 -0.42979092
age -0.1844848 0.1965657 0.01677137 -0.01591818
SexFemale:age 0.1751000 -0.4297909 -0.01591818 0.03907190
> summary(ma)
Call:
model.avg(object = gm, revised = F)
Component model call:
lm(formula = distance ~ <4 unique rhs>, data = Orthodont)
Component models:
df logLik AICc delta weight
123 5 -239.12 488.83 0.00 0.53
12 4 -240.34 489.07 0.24 0.47
2 3 -252.79 511.81 22.98 0.00
1 3 -259.82 525.87 37.04 0.00
Term codes:
Sex age Sex:age
1 2 3
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.1616 0.2094 0.2106 0.767 0.443
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.3048 0.1977 0.2000 1.524 0.127
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Running the tests in ‘tests/singularities.R’ failed.
Complete output:
> library(MuMIn)
> options(na.action = "na.fail")
>
> set.seed(1)
> zz <- data.frame(x=runif(15), f1=gl(3,5), f2=factor(rep(1:2,c(10,5))))
> zz$y <- 100*zz$x + as.numeric(zz$f1)*10 * as.numeric(zz$f2)
>
> nafit <- lm(y~f1*f2*x, zz)
>
> summary(nafit)
Call:
lm(formula = y ~ f1 * f2 * x, data = zz)
Residuals:
Min 1Q Median 3Q Max
-1.543e-14 -2.853e-15 2.200e-17 1.580e-15 2.483e-14
Coefficients: (6 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.000e+01 9.723e-15 1.028e+15 <2e-16 ***
f12 1.000e+01 1.439e-14 6.948e+14 <2e-16 ***
f13 5.000e+01 1.377e-14 3.631e+15 <2e-16 ***
f22 NA NA NA NA
x 1.000e+02 1.836e-14 5.447e+15 <2e-16 ***
f12:f22 NA NA NA NA
f13:f22 NA NA NA NA
f12:x 1.072e-14 2.364e-14 4.530e-01 0.661
f13:x 1.081e-14 2.658e-14 4.070e-01 0.694
f22:x NA NA NA NA
f12:f22:x NA NA NA NA
f13:f22:x NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.048e-14 on 9 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 3.094e+31 on 5 and 9 DF, p-value: < 2.2e-16
Warning message:
In summary.lm(nafit) : essentially perfect fit: summary may be unreliable
> coef(nafit)
(Intercept) f12 f13 f22 x f12:f22
1.000000e+01 1.000000e+01 5.000000e+01 NA 1.000000e+02 NA
f13:f22 f12:x f13:x f22:x f12:f22:x f13:f22:x
NA 1.071683e-14 1.081218e-14 NA NA NA
>
> gm <- get.models(dredge(nafit), subset = NA)
Fixed term is "(Intercept)"
There were 11 warnings (use warnings() to see them)
> ma <- model.avg(gm)
There were 11 warnings (use warnings() to see them)
>
> summary(ma)
Call:
model.avg(object = gm)
Component model call:
lm(formula = y ~ <19 unique rhs>, data = zz)
Component models:
df logLik AICc delta weight
13 5 465.19 -913.71 0.00 0.32
123 5 465.19 -913.71 0.00 0.32
1234 5 465.19 -913.71 0.00 0.32
1236 6 465.22 -907.94 5.77 0.02
12346 6 465.22 -907.94 5.77 0.02
135 7 465.39 -900.78 12.93 0.00
1235 7 465.39 -900.78 12.93 0.00
12345 7 465.39 -900.78 12.93 0.00
12356 7 465.39 -900.78 12.93 0.00
123456 7 465.39 -900.78 12.93 0.00
1234567 7 465.39 -900.78 12.93 0.00
23 4 -41.89 95.78 1009.49 0.00
236 5 -41.72 100.10 1013.81 0.00
3 3 -67.26 142.70 1056.41 0.00
2 3 -72.05 152.29 1066.00 0.00
(Null) 2 -74.03 153.05 1066.76 0.00
1 4 -70.88 153.77 1067.48 0.00
12 4 -70.88 153.77 1067.48 0.00
124 4 -70.88 153.77 1067.48 0.00
Term codes:
f1 f2 x f1:f2 f1:x f2:x f1:f2:x
1 2 3 4 5 6 7
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 1.011e-218 6.807e-109 6.810e-109 0.000e+00 1.000
f12:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f22:x 1.556e-16 4.151e-15 4.698e-15 3.300e-02 0.974
f12:x 3.202e-17 1.419e-15 1.602e-15 2.000e-02 0.984
f13:x 3.231e-17 1.568e-15 1.778e-15 1.800e-02 0.986
f12:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 4.563e+01 2.950e+00 3.273e+00 1.394e+01 <2e-16 ***
f12:f22 NA NA NA NA NA
f13:f22 NA NA NA NA NA
f22:x 4.352e-15 2.153e-14 2.448e-14 1.780e-01 0.859
f12:x 1.072e-14 2.364e-14 2.729e-14 3.930e-01 0.695
f13:x 1.081e-14 2.658e-14 3.068e-14 3.520e-01 0.725
f12:f22:x NA NA NA NA NA
f13:f22:x NA NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> coef(ma, T)
(Intercept) f12 f13 x f22
1.000000e+01 1.000000e+01 5.000000e+01 1.000000e+02 1.011128e-218
f12:f22 f13:f22 f22:x f12:x f13:x
0.000000e+00 0.000000e+00 1.556097e-16 3.202112e-17 3.230602e-17
f12:f22:x f13:f22:x
0.000000e+00 0.000000e+00
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.47.1
Check: tests
Result: ERROR
Running ‘gam-smooth-match.R’ [3s/5s]
Running ‘gam.R’ [3s/7s]
Running ‘glm.R’ [2s/4s]
Running ‘glm.nb.R’ [3s/4s]
Running ‘misc-tests.R’ [2s/4s]
Running ‘multinom.R’ [2s/3s]
Running ‘nlme.R’ [3s/4s]
Running ‘parallel.R’ [8s/17s]
Running ‘quasibinomial.R’ [2s/4s]
Running ‘rlm.R’ [2s/4s]
Running ‘singularities.R’ [2s/5s]
Running ‘survival.R’ [3s/6s]
Running the tests in ‘tests/glm.R’ failed.
Complete output:
> library("MuMIn")
> options(na.action = "na.fail")
> data(Orthodont, package = "nlme")
>
> fm1 <- lm(distance ~ Sex * age + age * Sex, data = Orthodont)
>
> dispersion <- function(object) {
+ wts <- weights(object)
+ if (is.null(wts))
+ wts <- 1
+ sum((wts * resid(object, type = "working")^2)[wts > 0])/df.residual(object)
+ }
>
> dd <- dredge(fm1, extra = alist(dispersion))
Fixed term is "(Intercept)"
> gm <- get.models(dd, subset = 1:4)
> ma <- model.avg(gm, revised = F)
>
> vcov(ma)
(Intercept) SexFemale age SexFemale:age
(Intercept) 2.1094155 -2.2423049 -0.18448478 0.17510000
SexFemale -2.2423049 5.5038392 0.19656574 -0.42979092
age -0.1844848 0.1965657 0.01677137 -0.01591818
SexFemale:age 0.1751000 -0.4297909 -0.01591818 0.03907190
> summary(ma)
Call:
model.avg(object = gm, revised = F)
Component model call:
lm(formula = distance ~ <4 unique rhs>, data = Orthodont)
Component models:
df logLik AICc delta weight
123 5 -239.12 488.83 0.00 0.53
12 4 -240.34 489.07 0.24 0.47
2 3 -252.79 511.81 22.98 0.00
1 3 -259.82 525.87 37.04 0.00
Term codes:
Sex age Sex:age
1 2 3
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.1616 0.2094 0.2106 0.767 0.443
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.3048 0.1977 0.2000 1.524 0.127
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Running the tests in ‘tests/singularities.R’ failed.
Complete output:
> library(MuMIn)
> options(na.action = "na.fail")
>
> set.seed(1)
> zz <- data.frame(x=runif(15), f1=gl(3,5), f2=factor(rep(1:2,c(10,5))))
> zz$y <- 100*zz$x + as.numeric(zz$f1)*10 * as.numeric(zz$f2)
>
> nafit <- lm(y~f1*f2*x, zz)
>
> summary(nafit)
Call:
lm(formula = y ~ f1 * f2 * x, data = zz)
Residuals:
Min 1Q Median 3Q Max
-1.543e-14 -2.853e-15 2.200e-17 1.580e-15 2.483e-14
Coefficients: (6 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.000e+01 9.723e-15 1.028e+15 <2e-16 ***
f12 1.000e+01 1.439e-14 6.948e+14 <2e-16 ***
f13 5.000e+01 1.377e-14 3.631e+15 <2e-16 ***
f22 NA NA NA NA
x 1.000e+02 1.836e-14 5.447e+15 <2e-16 ***
f12:f22 NA NA NA NA
f13:f22 NA NA NA NA
f12:x 1.072e-14 2.364e-14 4.530e-01 0.661
f13:x 1.081e-14 2.658e-14 4.070e-01 0.694
f22:x NA NA NA NA
f12:f22:x NA NA NA NA
f13:f22:x NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.048e-14 on 9 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 3.094e+31 on 5 and 9 DF, p-value: < 2.2e-16
Warning message:
In summary.lm(nafit) : essentially perfect fit: summary may be unreliable
> coef(nafit)
(Intercept) f12 f13 f22 x f12:f22
1.000000e+01 1.000000e+01 5.000000e+01 NA 1.000000e+02 NA
f13:f22 f12:x f13:x f22:x f12:f22:x f13:f22:x
NA 1.071683e-14 1.081218e-14 NA NA NA
>
> gm <- get.models(dredge(nafit), subset = NA)
Fixed term is "(Intercept)"
There were 11 warnings (use warnings() to see them)
> ma <- model.avg(gm)
There were 11 warnings (use warnings() to see them)
>
> summary(ma)
Call:
model.avg(object = gm)
Component model call:
lm(formula = y ~ <19 unique rhs>, data = zz)
Component models:
df logLik AICc delta weight
13 5 465.19 -913.71 0.00 0.32
123 5 465.19 -913.71 0.00 0.32
1234 5 465.19 -913.71 0.00 0.32
1236 6 465.22 -907.94 5.77 0.02
12346 6 465.22 -907.94 5.77 0.02
135 7 465.39 -900.78 12.93 0.00
1235 7 465.39 -900.78 12.93 0.00
12345 7 465.39 -900.78 12.93 0.00
12356 7 465.39 -900.78 12.93 0.00
123456 7 465.39 -900.78 12.93 0.00
1234567 7 465.39 -900.78 12.93 0.00
23 4 -41.89 95.78 1009.49 0.00
236 5 -41.72 100.10 1013.81 0.00
3 3 -67.26 142.70 1056.41 0.00
2 3 -72.05 152.29 1066.00 0.00
(Null) 2 -74.03 153.05 1066.76 0.00
1 4 -70.88 153.77 1067.48 0.00
12 4 -70.88 153.77 1067.48 0.00
124 4 -70.88 153.77 1067.48 0.00
Term codes:
f1 f2 x f1:f2 f1:x f2:x f1:f2:x
1 2 3 4 5 6 7
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 1.011e-218 6.807e-109 6.810e-109 0.000e+00 1.000
f12:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f22:x 1.556e-16 4.151e-15 4.698e-15 3.300e-02 0.974
f12:x 3.202e-17 1.419e-15 1.602e-15 2.000e-02 0.984
f13:x 3.231e-17 1.568e-15 1.778e-15 1.800e-02 0.986
f12:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 4.563e+01 2.950e+00 3.273e+00 1.394e+01 <2e-16 ***
f12:f22 NA NA NA NA NA
f13:f22 NA NA NA NA NA
f22:x 4.352e-15 2.153e-14 2.448e-14 1.780e-01 0.859
f12:x 1.072e-14 2.364e-14 2.729e-14 3.930e-01 0.695
f13:x 1.081e-14 2.658e-14 3.068e-14 3.520e-01 0.725
f12:f22:x NA NA NA NA NA
f13:f22:x NA NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> coef(ma, T)
(Intercept) f12 f13 x f22
1.000000e+01 1.000000e+01 5.000000e+01 1.000000e+02 1.011128e-218
f12:f22 f13:f22 f22:x f12:x f13:x
0.000000e+00 0.000000e+00 1.556097e-16 3.202112e-17 3.230602e-17
f12:f22:x f13:f22:x
0.000000e+00 0.000000e+00
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.47.1
Check: Rd cross-references
Result: NOTE
Undeclared packages ‘AICcmodavg’, ‘bbmle’, ‘glmulti’, ‘arm’, ‘performance’, ‘wgeesel’, ‘ape’, ‘bestglm’, ‘leaps’, ‘glmmTMB’, ‘brglm’, ‘quantreg’, ‘maxlike’, ‘RMark’ in Rd xrefs
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.47.1
Check: examples
Result: ERROR
Running examples in ‘MuMIn-Ex.R’ failed
The error most likely occurred in:
> ### Name: MuMIn-package
> ### Title: Multi-model inference
> ### Aliases: MuMIn-package MuMIn
> ### Keywords: package models
>
> ### ** Examples
>
> ## Don't show:
> oop <-
+ ## End(Don't show)
+ options(na.action = "na.fail") # change the default "na.omit" to prevent models
> # from being fitted to different datasets in
> # case of missing values.
>
> fm1 <- lm(y ~ ., data = Cement)
> ms1 <- dredge(fm1)
Fixed term is "(Intercept)"
>
> # Visualize the model selection table:
> ## Don't show:
> if(require(graphics)) {
+ ## End(Don't show)
+ par(mar = c(3,5,6,4))
+ plot(ms1, labAsExpr = TRUE)
+ ## Don't show:
+ }
> ## End(Don't show)
> model.avg(ms1, subset = delta < 4)
Call:
model.avg(object = ms1, subset = delta < 4)
Component models:
‘12’ ‘124’ ‘123’ ‘14’ ‘134’
Coefficients:
(Intercept) X1 X2 X4 X3
full 64.69313 1.455798 0.5057578 -0.1478697 -0.004302377
subset 64.69313 1.455798 0.6250260 -0.4760071 -0.021531961
>
> confset.95p <- get.models(ms1, cumsum(weight) <= .95)
> avgmod.95p <- model.avg(confset.95p)
> summary(avgmod.95p)
Call:
model.avg(object = confset.95p)
Component model call:
lm(formula = y ~ <4 unique rhs>, data = Cement)
Component models:
df logLik AICc delta weight
12 4 -28.16 69.31 0.00 0.62
124 5 -26.93 72.44 3.13 0.13
123 5 -26.95 72.48 3.16 0.13
14 4 -29.82 72.63 3.32 0.12
Term codes:
X1 X2 X3 X4
1 2 3 4
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 60.48430 17.92604 18.21471 3.321 0.000898 ***
X1 1.49198 0.15745 0.17467 8.542 < 2e-16 ***
X2 0.55106 0.23133 0.23552 2.340 0.019299 *
X4 -0.10354 0.21306 0.21628 0.479 0.632129
X3 0.03204 0.10656 0.11317 0.283 0.777105
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 60.4843 17.9260 18.2147 3.321 0.000898 ***
X1 1.4920 0.1575 0.1747 8.542 < 2e-16 ***
X2 0.6250 0.1203 0.1292 4.839 1.31e-06 ***
X4 -0.4160 0.2289 0.2408 1.728 0.084009 .
X3 0.2500 0.1847 0.2132 1.173 0.240898
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> confint(avgmod.95p)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64
Version: 1.47.1
Check: tests
Result: ERROR
Running ‘gam-smooth-match.R’ [5s/13s]
Running ‘gam.R’ [6s/13s]
Running ‘glm.R’
Running ‘glm.nb.R’ [5s/12s]
Running ‘misc-tests.R’ [4s/11s]
Running ‘multinom.R’
Running ‘nlme.R’ [5s/12s]
Running ‘parallel.R’ [13s/49s]
Running ‘quasibinomial.R’
Running ‘rlm.R’
Running ‘singularities.R’
Running ‘survival.R’ [5s/12s]
Running the tests in ‘tests/glm.R’ failed.
Complete output:
> library("MuMIn")
> options(na.action = "na.fail")
> data(Orthodont, package = "nlme")
>
> fm1 <- lm(distance ~ Sex * age + age * Sex, data = Orthodont)
>
> dispersion <- function(object) {
+ wts <- weights(object)
+ if (is.null(wts))
+ wts <- 1
+ sum((wts * resid(object, type = "working")^2)[wts > 0])/df.residual(object)
+ }
>
> dd <- dredge(fm1, extra = alist(dispersion))
Fixed term is "(Intercept)"
> gm <- get.models(dd, subset = 1:4)
> ma <- model.avg(gm, revised = F)
>
> vcov(ma)
(Intercept) SexFemale age SexFemale:age
(Intercept) 2.1094155 -2.2423049 -0.18448478 0.17510000
SexFemale -2.2423049 5.5038392 0.19656574 -0.42979092
age -0.1844848 0.1965657 0.01677137 -0.01591818
SexFemale:age 0.1751000 -0.4297909 -0.01591818 0.03907190
> summary(ma)
Call:
model.avg(object = gm, revised = F)
Component model call:
lm(formula = distance ~ <4 unique rhs>, data = Orthodont)
Component models:
df logLik AICc delta weight
123 5 -239.12 488.83 0.00 0.53
12 4 -240.34 489.07 0.24 0.47
2 3 -252.79 511.81 22.98 0.00
1 3 -259.82 525.87 37.04 0.00
Term codes:
Sex age Sex:age
1 2 3
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.1616 0.2094 0.2106 0.767 0.443
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.3048 0.1977 0.2000 1.524 0.127
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Running the tests in ‘tests/singularities.R’ failed.
Complete output:
> library(MuMIn)
> options(na.action = "na.fail")
>
> set.seed(1)
> zz <- data.frame(x=runif(15), f1=gl(3,5), f2=factor(rep(1:2,c(10,5))))
> zz$y <- 100*zz$x + as.numeric(zz$f1)*10 * as.numeric(zz$f2)
>
> nafit <- lm(y~f1*f2*x, zz)
>
> summary(nafit)
Call:
lm(formula = y ~ f1 * f2 * x, data = zz)
Residuals:
Min 1Q Median 3Q Max
-1.543e-14 -2.853e-15 2.200e-17 1.580e-15 2.483e-14
Coefficients: (6 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.000e+01 9.723e-15 1.028e+15 <2e-16 ***
f12 1.000e+01 1.439e-14 6.948e+14 <2e-16 ***
f13 5.000e+01 1.377e-14 3.631e+15 <2e-16 ***
f22 NA NA NA NA
x 1.000e+02 1.836e-14 5.447e+15 <2e-16 ***
f12:f22 NA NA NA NA
f13:f22 NA NA NA NA
f12:x 1.072e-14 2.364e-14 4.530e-01 0.661
f13:x 1.081e-14 2.658e-14 4.070e-01 0.694
f22:x NA NA NA NA
f12:f22:x NA NA NA NA
f13:f22:x NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.048e-14 on 9 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 3.094e+31 on 5 and 9 DF, p-value: < 2.2e-16
Warning message:
In summary.lm(nafit) : essentially perfect fit: summary may be unreliable
> coef(nafit)
(Intercept) f12 f13 f22 x f12:f22
1.000000e+01 1.000000e+01 5.000000e+01 NA 1.000000e+02 NA
f13:f22 f12:x f13:x f22:x f12:f22:x f13:f22:x
NA 1.071683e-14 1.081218e-14 NA NA NA
>
> gm <- get.models(dredge(nafit), subset = NA)
Fixed term is "(Intercept)"
There were 11 warnings (use warnings() to see them)
> ma <- model.avg(gm)
There were 11 warnings (use warnings() to see them)
>
> summary(ma)
Call:
model.avg(object = gm)
Component model call:
lm(formula = y ~ <19 unique rhs>, data = zz)
Component models:
df logLik AICc delta weight
13 5 465.19 -913.71 0.00 0.32
123 5 465.19 -913.71 0.00 0.32
1234 5 465.19 -913.71 0.00 0.32
1236 6 465.22 -907.94 5.77 0.02
12346 6 465.22 -907.94 5.77 0.02
135 7 465.39 -900.78 12.93 0.00
1235 7 465.39 -900.78 12.93 0.00
12345 7 465.39 -900.78 12.93 0.00
12356 7 465.39 -900.78 12.93 0.00
123456 7 465.39 -900.78 12.93 0.00
1234567 7 465.39 -900.78 12.93 0.00
23 4 -41.89 95.78 1009.49 0.00
236 5 -41.72 100.10 1013.81 0.00
3 3 -67.26 142.70 1056.41 0.00
2 3 -72.05 152.29 1066.00 0.00
(Null) 2 -74.03 153.05 1066.76 0.00
1 4 -70.88 153.77 1067.48 0.00
12 4 -70.88 153.77 1067.48 0.00
124 4 -70.88 153.77 1067.48 0.00
Term codes:
f1 f2 x f1:f2 f1:x f2:x f1:f2:x
1 2 3 4 5 6 7
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 1.011e-218 6.807e-109 6.810e-109 0.000e+00 1.000
f12:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f22:x 1.556e-16 4.151e-15 4.698e-15 3.300e-02 0.974
f12:x 3.202e-17 1.419e-15 1.602e-15 2.000e-02 0.984
f13:x 3.231e-17 1.568e-15 1.778e-15 1.800e-02 0.986
f12:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 4.563e+01 2.950e+00 3.273e+00 1.394e+01 <2e-16 ***
f12:f22 NA NA NA NA NA
f13:f22 NA NA NA NA NA
f22:x 4.352e-15 2.153e-14 2.448e-14 1.780e-01 0.859
f12:x 1.072e-14 2.364e-14 2.729e-14 3.930e-01 0.695
f13:x 1.081e-14 2.658e-14 3.068e-14 3.520e-01 0.725
f12:f22:x NA NA NA NA NA
f13:f22:x NA NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> coef(ma, T)
(Intercept) f12 f13 x f22
1.000000e+01 1.000000e+01 5.000000e+01 1.000000e+02 1.011128e-218
f12:f22 f13:f22 f22:x f12:x f13:x
0.000000e+00 0.000000e+00 1.556097e-16 3.202112e-17 3.230602e-17
f12:f22:x f13:f22:x
0.000000e+00 0.000000e+00
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.47.1
Check: tests
Result: ERROR
Running ‘gam-smooth-match.R’ [5s/14s]
Running ‘gam.R’ [6s/21s]
Running ‘glm.R’ [4s/14s]
Running ‘glm.nb.R’ [5s/16s]
Running ‘misc-tests.R’
Running ‘multinom.R’ [4s/14s]
Running ‘nlme.R’ [5s/17s]
Running ‘parallel.R’ [13s/59s]
Running ‘quasibinomial.R’
Running ‘rlm.R’ [4s/12s]
Running ‘singularities.R’ [4s/11s]
Running ‘survival.R’ [5s/20s]
Running the tests in ‘tests/glm.R’ failed.
Complete output:
> library("MuMIn")
> options(na.action = "na.fail")
> data(Orthodont, package = "nlme")
>
> fm1 <- lm(distance ~ Sex * age + age * Sex, data = Orthodont)
>
> dispersion <- function(object) {
+ wts <- weights(object)
+ if (is.null(wts))
+ wts <- 1
+ sum((wts * resid(object, type = "working")^2)[wts > 0])/df.residual(object)
+ }
>
> dd <- dredge(fm1, extra = alist(dispersion))
Fixed term is "(Intercept)"
> gm <- get.models(dd, subset = 1:4)
> ma <- model.avg(gm, revised = F)
>
> vcov(ma)
(Intercept) SexFemale age SexFemale:age
(Intercept) 2.1094155 -2.2423049 -0.18448478 0.17510000
SexFemale -2.2423049 5.5038392 0.19656574 -0.42979092
age -0.1844848 0.1965657 0.01677137 -0.01591818
SexFemale:age 0.1751000 -0.4297909 -0.01591818 0.03907190
> summary(ma)
Call:
model.avg(object = gm, revised = F)
Component model call:
lm(formula = distance ~ <4 unique rhs>, data = Orthodont)
Component models:
df logLik AICc delta weight
123 5 -239.12 488.83 0.00 0.53
12 4 -240.34 489.07 0.24 0.47
2 3 -252.79 511.81 22.98 0.00
1 3 -259.82 525.87 37.04 0.00
Term codes:
Sex age Sex:age
1 2 3
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.1616 0.2094 0.2106 0.767 0.443
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.3048 0.1977 0.2000 1.524 0.127
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Running the tests in ‘tests/singularities.R’ failed.
Complete output:
> library(MuMIn)
> options(na.action = "na.fail")
>
> set.seed(1)
> zz <- data.frame(x=runif(15), f1=gl(3,5), f2=factor(rep(1:2,c(10,5))))
> zz$y <- 100*zz$x + as.numeric(zz$f1)*10 * as.numeric(zz$f2)
>
> nafit <- lm(y~f1*f2*x, zz)
>
> summary(nafit)
Call:
lm(formula = y ~ f1 * f2 * x, data = zz)
Residuals:
Min 1Q Median 3Q Max
-1.543e-14 -2.853e-15 2.200e-17 1.580e-15 2.483e-14
Coefficients: (6 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.000e+01 9.723e-15 1.028e+15 <2e-16 ***
f12 1.000e+01 1.439e-14 6.948e+14 <2e-16 ***
f13 5.000e+01 1.377e-14 3.631e+15 <2e-16 ***
f22 NA NA NA NA
x 1.000e+02 1.836e-14 5.447e+15 <2e-16 ***
f12:f22 NA NA NA NA
f13:f22 NA NA NA NA
f12:x 1.072e-14 2.364e-14 4.530e-01 0.661
f13:x 1.081e-14 2.658e-14 4.070e-01 0.694
f22:x NA NA NA NA
f12:f22:x NA NA NA NA
f13:f22:x NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.048e-14 on 9 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 3.094e+31 on 5 and 9 DF, p-value: < 2.2e-16
Warning message:
In summary.lm(nafit) : essentially perfect fit: summary may be unreliable
> coef(nafit)
(Intercept) f12 f13 f22 x f12:f22
1.000000e+01 1.000000e+01 5.000000e+01 NA 1.000000e+02 NA
f13:f22 f12:x f13:x f22:x f12:f22:x f13:f22:x
NA 1.071683e-14 1.081218e-14 NA NA NA
>
> gm <- get.models(dredge(nafit), subset = NA)
Fixed term is "(Intercept)"
There were 11 warnings (use warnings() to see them)
> ma <- model.avg(gm)
There were 11 warnings (use warnings() to see them)
>
> summary(ma)
Call:
model.avg(object = gm)
Component model call:
lm(formula = y ~ <19 unique rhs>, data = zz)
Component models:
df logLik AICc delta weight
13 5 465.19 -913.71 0.00 0.32
123 5 465.19 -913.71 0.00 0.32
1234 5 465.19 -913.71 0.00 0.32
1236 6 465.22 -907.94 5.77 0.02
12346 6 465.22 -907.94 5.77 0.02
135 7 465.39 -900.78 12.93 0.00
1235 7 465.39 -900.78 12.93 0.00
12345 7 465.39 -900.78 12.93 0.00
12356 7 465.39 -900.78 12.93 0.00
123456 7 465.39 -900.78 12.93 0.00
1234567 7 465.39 -900.78 12.93 0.00
23 4 -41.89 95.78 1009.49 0.00
236 5 -41.72 100.10 1013.81 0.00
3 3 -67.26 142.70 1056.41 0.00
2 3 -72.05 152.29 1066.00 0.00
(Null) 2 -74.03 153.05 1066.76 0.00
1 4 -70.88 153.77 1067.48 0.00
12 4 -70.88 153.77 1067.48 0.00
124 4 -70.88 153.77 1067.48 0.00
Term codes:
f1 f2 x f1:f2 f1:x f2:x f1:f2:x
1 2 3 4 5 6 7
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 1.011e-218 6.807e-109 6.810e-109 0.000e+00 1.000
f12:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f22:x 1.556e-16 4.151e-15 4.698e-15 3.300e-02 0.974
f12:x 3.202e-17 1.419e-15 1.602e-15 2.000e-02 0.984
f13:x 3.231e-17 1.568e-15 1.778e-15 1.800e-02 0.986
f12:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 4.563e+01 2.950e+00 3.273e+00 1.394e+01 <2e-16 ***
f12:f22 NA NA NA NA NA
f13:f22 NA NA NA NA NA
f22:x 4.352e-15 2.153e-14 2.448e-14 1.780e-01 0.859
f12:x 1.072e-14 2.364e-14 2.729e-14 3.930e-01 0.695
f13:x 1.081e-14 2.658e-14 3.068e-14 3.520e-01 0.725
f12:f22:x NA NA NA NA NA
f13:f22:x NA NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> coef(ma, T)
(Intercept) f12 f13 x f22
1.000000e+01 1.000000e+01 5.000000e+01 1.000000e+02 1.011128e-218
f12:f22 f13:f22 f22:x f12:x f13:x
0.000000e+00 0.000000e+00 1.556097e-16 3.202112e-17 3.230602e-17
f12:f22:x f13:f22:x
0.000000e+00 0.000000e+00
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.47.1
Check: tests
Result: ERROR
Running 'gam-smooth-match.R' [4s]
Running 'gam.R' [5s]
Running 'glm.R' [3s]
Running 'glm.nb.R' [4s]
Running 'misc-tests.R' [3s]
Running 'multinom.R' [3s]
Running 'nlme.R' [4s]
Running 'parallel.R' [15s]
Running 'quasibinomial.R' [3s]
Running 'rlm.R' [3s]
Running 'singularities.R' [3s]
Running 'survival.R' [4s]
Running the tests in 'tests/glm.R' failed.
Complete output:
> library("MuMIn")
> options(na.action = "na.fail")
> data(Orthodont, package = "nlme")
>
> fm1 <- lm(distance ~ Sex * age + age * Sex, data = Orthodont)
>
> dispersion <- function(object) {
+ wts <- weights(object)
+ if (is.null(wts))
+ wts <- 1
+ sum((wts * resid(object, type = "working")^2)[wts > 0])/df.residual(object)
+ }
>
> dd <- dredge(fm1, extra = alist(dispersion))
Fixed term is "(Intercept)"
> gm <- get.models(dd, subset = 1:4)
> ma <- model.avg(gm, revised = F)
>
> vcov(ma)
(Intercept) SexFemale age SexFemale:age
(Intercept) 2.1094155 -2.2423049 -0.18448478 0.17510000
SexFemale -2.2423049 5.5038392 0.19656574 -0.42979092
age -0.1844848 0.1965657 0.01677137 -0.01591818
SexFemale:age 0.1751000 -0.4297909 -0.01591818 0.03907190
> summary(ma)
Call:
model.avg(object = gm, revised = F)
Component model call:
lm(formula = distance ~ <4 unique rhs>, data = Orthodont)
Component models:
df logLik AICc delta weight
123 5 -239.12 488.83 0.00 0.53
12 4 -240.34 489.07 0.24 0.47
2 3 -252.79 511.81 22.98 0.00
1 3 -259.82 525.87 37.04 0.00
Term codes:
Sex age Sex:age
1 2 3
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.1616 0.2094 0.2106 0.767 0.443
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 16.9824 1.4524 1.4657 11.587 <2e-16 ***
SexFemale -0.5432 2.3460 2.3596 0.230 0.818
age 0.7260 0.1295 0.1307 5.556 <2e-16 ***
SexFemale:age -0.3048 0.1977 0.2000 1.524 0.127
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Running the tests in 'tests/singularities.R' failed.
Complete output:
> library(MuMIn)
> options(na.action = "na.fail")
>
> set.seed(1)
> zz <- data.frame(x=runif(15), f1=gl(3,5), f2=factor(rep(1:2,c(10,5))))
> zz$y <- 100*zz$x + as.numeric(zz$f1)*10 * as.numeric(zz$f2)
>
> nafit <- lm(y~f1*f2*x, zz)
>
> summary(nafit)
Call:
lm(formula = y ~ f1 * f2 * x, data = zz)
Residuals:
Min 1Q Median 3Q Max
-1.543e-14 -2.853e-15 2.200e-17 1.580e-15 2.483e-14
Coefficients: (6 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.000e+01 9.723e-15 1.028e+15 <2e-16 ***
f12 1.000e+01 1.439e-14 6.948e+14 <2e-16 ***
f13 5.000e+01 1.377e-14 3.631e+15 <2e-16 ***
f22 NA NA NA NA
x 1.000e+02 1.836e-14 5.447e+15 <2e-16 ***
f12:f22 NA NA NA NA
f13:f22 NA NA NA NA
f12:x 1.072e-14 2.364e-14 4.530e-01 0.661
f13:x 1.081e-14 2.658e-14 4.070e-01 0.694
f22:x NA NA NA NA
f12:f22:x NA NA NA NA
f13:f22:x NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.048e-14 on 9 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 3.094e+31 on 5 and 9 DF, p-value: < 2.2e-16
Warning message:
In summary.lm(nafit) : essentially perfect fit: summary may be unreliable
> coef(nafit)
(Intercept) f12 f13 f22 x f12:f22
1.000000e+01 1.000000e+01 5.000000e+01 NA 1.000000e+02 NA
f13:f22 f12:x f13:x f22:x f12:f22:x f13:f22:x
NA 1.071683e-14 1.081218e-14 NA NA NA
>
> gm <- get.models(dredge(nafit), subset = NA)
Fixed term is "(Intercept)"
There were 11 warnings (use warnings() to see them)
> ma <- model.avg(gm)
There were 11 warnings (use warnings() to see them)
>
> summary(ma)
Call:
model.avg(object = gm)
Component model call:
lm(formula = y ~ <19 unique rhs>, data = zz)
Component models:
df logLik AICc delta weight
13 5 465.19 -913.71 0.00 0.32
123 5 465.19 -913.71 0.00 0.32
1234 5 465.19 -913.71 0.00 0.32
1236 6 465.22 -907.94 5.77 0.02
12346 6 465.22 -907.94 5.77 0.02
135 7 465.39 -900.78 12.93 0.00
1235 7 465.39 -900.78 12.93 0.00
12345 7 465.39 -900.78 12.93 0.00
12356 7 465.39 -900.78 12.93 0.00
123456 7 465.39 -900.78 12.93 0.00
1234567 7 465.39 -900.78 12.93 0.00
23 4 -41.89 95.78 1009.49 0.00
236 5 -41.72 100.10 1013.81 0.00
3 3 -67.26 142.70 1056.41 0.00
2 3 -72.05 152.29 1066.00 0.00
(Null) 2 -74.03 153.05 1066.76 0.00
1 4 -70.88 153.77 1067.48 0.00
12 4 -70.88 153.77 1067.48 0.00
124 4 -70.88 153.77 1067.48 0.00
Term codes:
f1 f2 x f1:f2 f1:x f2:x f1:f2:x
1 2 3 4 5 6 7
Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 1.011e-218 6.807e-109 6.810e-109 0.000e+00 1.000
f12:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f22:x 1.556e-16 4.151e-15 4.698e-15 3.300e-02 0.974
f12:x 3.202e-17 1.419e-15 1.602e-15 2.000e-02 0.984
f13:x 3.231e-17 1.568e-15 1.778e-15 1.800e-02 0.986
f12:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
f13:f22:x 0.000e+00 0.000e+00 0.000e+00 NaN NaN
(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) 1.000e+01 6.326e-15 7.049e-15 1.419e+15 <2e-16 ***
f12 1.000e+01 6.594e-15 7.351e-15 1.360e+15 <2e-16 ***
f13 5.000e+01 6.405e-15 7.203e-15 6.942e+15 <2e-16 ***
x 1.000e+02 1.693e-14 1.758e-14 5.688e+15 <2e-16 ***
f22 4.563e+01 2.950e+00 3.273e+00 1.394e+01 <2e-16 ***
f12:f22 NA NA NA NA NA
f13:f22 NA NA NA NA NA
f22:x 4.352e-15 2.153e-14 2.448e-14 1.780e-01 0.859
f12:x 1.072e-14 2.364e-14 2.729e-14 3.930e-01 0.695
f13:x 1.081e-14 2.658e-14 3.068e-14 3.520e-01 0.725
f12:f22:x NA NA NA NA NA
f13:f22:x NA NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> coef(ma, T)
(Intercept) f12 f13 x f22
1.000000e+01 1.000000e+01 5.000000e+01 1.000000e+02 1.011128e-218
f12:f22 f13:f22 f22:x f12:x f13:x
0.000000e+00 0.000000e+00 1.556097e-16 3.202112e-17 3.230602e-17
f12:f22:x f13:f22:x
0.000000e+00 0.000000e+00
> confint(ma)
Error in get(name, envir = asNamespace(pkg), inherits = FALSE) :
object 'format.perc' not found
Calls: confint -> confint.averaging -> getFrom -> get
Execution halted
Flavor: r-devel-windows-x86_64