Last updated on 2026-07-08 01:52:47 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.15-3 | 10.76 | 95.89 | 106.65 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.15-3 | 9.13 | 67.58 | 76.71 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.15-3 | 23.00 | 152.53 | 175.53 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.15-3 | 24.00 | 154.96 | 178.96 | OK | |
| r-devel-windows-x86_64 | 1.15-3 | 15.00 | 108.00 | 123.00 | OK | |
| r-patched-linux-x86_64 | 1.15-3 | 13.52 | 91.90 | 105.42 | OK | |
| r-release-linux-x86_64 | 1.15-3 | 13.36 | 90.83 | 104.19 | OK | |
| r-release-macos-arm64 | 1.15-3 | 3.00 | 23.00 | 26.00 | OK | |
| r-release-macos-x86_64 | 1.15-3 | 9.00 | 84.00 | 93.00 | OK | |
| r-release-windows-x86_64 | 1.15-3 | 13.00 | 111.00 | 124.00 | OK | |
| r-oldrel-macos-arm64 | 1.15-3 | 3.00 | 23.00 | 26.00 | OK | |
| r-oldrel-macos-x86_64 | 1.15-3 | 9.00 | 100.00 | 109.00 | OK | |
| r-oldrel-windows-x86_64 | 1.15-3 | 22.00 | 135.00 | 157.00 | OK |
Version: 1.15-3
Check: examples
Result: ERROR
Running examples in ‘arm-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: sim
> ### Title: Functions to Get Posterior Distributions
> ### Aliases: sim sim-class sim.merMod-class sim,lm-method sim,glm-method
> ### sim,polr-method sim,merMod-method coef.sim coef.sim.polr
> ### coef.sim.merMod fixef.sim.merMod ranef.sim.merMod fitted.sim.merMod
> ### Keywords: models methods
>
> ### ** Examples
>
> #Examples of "sim"
> set.seed (1)
> J <- 15
> n <- J*(J+1)/2
> group <- rep (1:J, 1:J)
> mu.a <- 5
> sigma.a <- 2
> a <- rnorm (J, mu.a, sigma.a)
> b <- -3
> x <- rnorm (n, 2, 1)
> sigma.y <- 6
> y <- rnorm (n, a[group] + b*x, sigma.y)
> u <- runif (J, 0, 3)
> y123.dat <- cbind (y, x, group)
> # Linear regression
> x1 <- y123.dat[,2]
> y1 <- y123.dat[,1]
> M1 <- lm (y1 ~ x1)
> display(M1)
lm(formula = y1 ~ x1)
coef.est coef.se
(Intercept) 5.79 1.72
x1 -3.42 0.77
---
n = 120, k = 2
residual sd = 7.04, R-Squared = 0.14
> M1.sim <- sim(M1)
> coef.M1.sim <- coef(M1.sim)
> sigma.M1.sim <- sigma.hat(M1.sim)
> ## to get the uncertainty for the simulated estimates
> apply(coef(M1.sim), 2, quantile)
(Intercept) x1
0% -0.6965736 -5.0647624
25% 4.7131084 -3.9309356
50% 6.0346236 -3.4834091
75% 6.9481385 -2.9938647
100% 9.4221294 -0.3620188
> quantile(sigma.hat(M1.sim))
0% 25% 50% 75% 100%
6.159272 6.772798 7.065009 7.484341 8.345240
>
> # Logistic regression
> u.data <- cbind (1:J, u)
> dimnames(u.data)[[2]] <- c("group", "u")
> u.dat <- as.data.frame (u.data)
> y <- rbinom (n, 1, invlogit (a[group] + b*x))
> M2 <- glm (y ~ x, family=binomial(link="logit"))
> display(M2)
glm(formula = y ~ x, family = binomial(link = "logit"))
coef.est coef.se
(Intercept) 4.52 0.97
x -2.64 0.51
---
n = 120, k = 2
residual deviance = 102.3, null deviance = 157.7 (difference = 55.4)
> M2.sim <- sim (M2)
> coef.M2.sim <- coef(M2.sim)
> sigma.M2.sim <- sigma.hat(M2.sim)
>
> # Ordered Logistic regression
> house.plr <- polr(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
> display(house.plr)
Re-fitting to get Hessian
polr(formula = Sat ~ Infl + Type + Cont, data = housing, weights = Freq)
coef.est coef.se
InflMedium 0.57 0.10
InflHigh 1.29 0.13
TypeApartment -0.57 0.12
TypeAtrium -0.37 0.16
TypeTerrace -1.09 0.15
ContHigh 0.36 0.10
Low|Medium -0.50 0.12
Medium|High 0.69 0.13
---
n = 1681, k = 8 (including 2 intercepts)
residual deviance = 3479.1, null deviance is not computed by polr
> M.plr <- sim(house.plr)
Re-fitting to get Hessian
> coef.sim <- coef(M.plr, slot="coef")
> zeta.sim <- coef(M.plr, slot="zeta")
> coefall.sim <- coef(M.plr)
>
> # Using lmer:
> # Example 1
> E1 <- lmer (y ~ x + (1 | group))
> display(E1)
lmer(formula = y ~ x + (1 | group))
coef.est coef.se
(Intercept) 1.02 0.10
x -0.32 0.04
Error terms:
Groups Name Std.Dev.
group (Intercept) 0.17
Residual 0.34
---
number of obs: 120, groups: group, 15
AIC = 115, DIC = 89.8
deviance = 98.4
> E1.sim <- sim (E1)
> coef.E1.sim <- coef(E1.sim)
> fixef.E1.sim <- fixef(E1.sim)
> ranef.E1.sim <- ranef(E1.sim)
> sigma.E1.sim <- sigma.hat(E1.sim)
> yhat <- fitted(E1.sim, E1)
>
> # Example 2
> u.full <- u[group]
> E2 <- lmer (y ~ x + u.full + (1 | group))
> display(E2)
lmer(formula = y ~ x + u.full + (1 | group))
coef.est coef.se
(Intercept) 0.92 0.16
x -0.32 0.04
u.full 0.07 0.08
Error terms:
Groups Name Std.Dev.
group (Intercept) 0.17
Residual 0.35
---
number of obs: 120, groups: group, 15
AIC = 119.5, DIC = 85.6
deviance = 97.6
> E2.sim <- sim (E2)
> coef.E2.sim <- coef(E2.sim)
> fixef.E2.sim <- fixef(E2.sim)
> ranef.E2.sim <- ranef(E2.sim)
> sigma.E2.sim <- sigma.hat(E2.sim)
> yhat <- fitted(E2.sim, E2)
>
> # Example 3
> y <- rbinom (n, 1, invlogit (a[group] + b*x))
> E3 <- glmer (y ~ x + (1 | group), family=binomial(link="logit"))
Error: Downdated VtV is not positive definite
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc