Running examples in 'VGAM-Ex.R' failed
The error most likely occurred in:

> ### Name: normal.vcm
> ### Title: Univariate Normal Distribution as a Varying-Coefficient Model
> ### Aliases: normal.vcm
> ### Keywords: models regression
> 
> ### ** Examples
> 
> ndata <- data.frame(x2 = runif(nn <- 2000))
> # Note that coeff1 + coeff2 + coeff5 == 1. So try "multilogitlink".
> myoffset <- 10
> ndata <- transform(ndata,
+            coeff1 = 0.25,  # "multilogitlink"
+            coeff2 = 0.25,  # "multilogitlink"
+            coeff3 = exp(-0.5),  # "loglink"
+ # "logofflink" link:
+            coeff4 = logofflink(+0.5, offset = myoffset, inverse = TRUE),
+            coeff5 = 0.50,  # "multilogitlink"
+            coeff6 = 1.00,  # "identitylink"
+            v2 = runif(nn),
+            v3 = runif(nn),
+            v4 = runif(nn),
+            v5 = rnorm(nn),
+            v6 = rnorm(nn))
> ndata <- transform(ndata,
+            Coeff1 =              0.25 - 0 * x2,
+            Coeff2 =              0.25 - 0 * x2,
+            Coeff3 =   logitlink(-0.5  - 1 * x2, inverse = TRUE),
+            Coeff4 =  logloglink( 0.5  - 1 * x2, inverse = TRUE),
+            Coeff5 =              0.50 - 0 * x2,
+            Coeff6 =              1.00 + 1 * x2)
> ndata <- transform(ndata,
+                    y1 = coeff1 * 1 +
+                         coeff2 * v2 +
+                         coeff3 * v3 +
+                         coeff4 * v4 +
+                         coeff5 * v5 +
+                         coeff6 * v6 + rnorm(nn, sd = exp(0)),
+                    y2 = Coeff1 * 1 +
+                         Coeff2 * v2 +
+                         Coeff3 * v3 +
+                         Coeff4 * v4 +
+                         Coeff5 * v5 +
+                         Coeff6 * v6 + rnorm(nn, sd = exp(0)))
> 
> # An intercept-only model
> fit1 <- vglm(y1 ~ 1,
+              form2 = ~ 1 + v2 + v3 + v4 + v5 + v6,
+              normal.vcm(link.list = list("(Intercept)" = "multilogitlink",
+                                          "v2"          = "multilogitlink",
+                                          "v3"          = "loglink",
+                                          "v4"          = "logofflink",
+                                          "(Default)"   = "identitylink",
+                                          "v5"          = "multilogitlink"),
+                         earg.list = list("(Intercept)" = list(),
+                                          "v2"          = list(),
+                                          "v4"          = list(offset = myoffset),
+                                          "v3"          = list(),
+                                          "(Default)"   = list(),
+                                          "v5"          = list()),
+                         zero = c(1:2, 6)),
+              data = ndata, trace = TRUE)
VGLM    linear loop  1 :  loglikelihood = -3169.92912
VGLM    linear loop  2 :  loglikelihood = -2865.38835
VGLM    linear loop  3 :  loglikelihood = -2808.43256
VGLM    linear loop  4 :  loglikelihood = -2806.74765
VGLM    linear loop  5 :  loglikelihood = -2806.74623
VGLM    linear loop  6 :  loglikelihood = -2806.74623
> coef(fit1, matrix = TRUE)
            multilogitlink(coeff:(Intercept)) multilogitlink(coeff:v2)
(Intercept)                        -0.8150088                -0.442383
            loglink(coeff:v3) logofflink(coeff:v4, offset = 10) coeff:v6
(Intercept)        -0.5381064                         0.5199879 1.021546
            loglink(sd)
(Intercept) -0.01556542
> summary(fit1)

Call:
vglm(formula = y1 ~ 1, family = normal.vcm(link.list = list(`(Intercept)` = "multilogitlink", 
    v2 = "multilogitlink", v3 = "loglink", v4 = "logofflink", 
    `(Default)` = "identitylink", v5 = "multilogitlink"), earg.list = list(`(Intercept)` = list(), 
    v2 = list(), v4 = list(offset = myoffset), v3 = list(), `(Default)` = list(), 
    v5 = list()), zero = c(1:2, 6)), data = ndata, form2 = ~1 + 
    v2 + v3 + v4 + v5 + v6, trace = TRUE)

Coefficients: 
              Estimate Std. Error z value Pr(>|z|)    
(Intercept):1 -0.81501    0.30485  -2.673  0.00751 ** 
(Intercept):2 -0.44238    0.21745  -2.034  0.04191 *  
(Intercept):3 -0.53811    0.11090  -4.852 1.22e-06 ***
(Intercept):4  0.51999    0.03882  13.396  < 2e-16 ***
(Intercept):5  1.02155    0.02161  47.278  < 2e-16 ***
(Intercept):6 -0.01557    0.01581  -0.984  0.32490    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Number of linear predictors:  6 

Names of linear predictors: multilogitlink(coeff:(Intercept)), 
multilogitlink(coeff:v2), loglink(coeff:v3), logofflink(coeff:v4, offset = 10), 
coeff:v6, loglink(sd)

Log-likelihood: -2806.746 on 11994 degrees of freedom

Number of Fisher scoring iterations: 6 

> # This works only for intercept-only models:
> multilogitlink(rbind(coef(fit1, matrix = TRUE)[1, c(1, 2)]), inverse = TRUE)
         [,1]      [,2]      [,3]
[1,] 0.212281 0.3081346 0.4795843
> 
> # A model with covariate x2 for the regression coefficients
> fit2 <- vglm(y2 ~ 1 + x2,
+              form2 = ~ 1 + v2 + v3 + v4 + v5 + v6,
+              normal.vcm(link.list = list("(Intercept)" = "multilogitlink",
+                                          "v2"          = "multilogitlink",
+                                          "v3"          = "logitlink",
+                                          "v4"          = "logloglink",
+                                          "(Default)"   = "identitylink",
+                                          "v5"          = "multilogitlink"),
+                         earg.list = list("(Intercept)" = list(),
+                                          "v2"          = list(),
+                                          "v3"          = list(),
+                                          "v4"          = list(),
+                                          "(Default)"   = list(),
+                                          "v5"          = list()),
+                         zero = c(1:2, 6)),
+              data = ndata, trace = TRUE)
Error: cannot allocate vector of size 328 Kb
Execution halted