message("1. Set seed as gnm returns random parameterization")
set.seed(1)
{
if (interactive()) {
cat("\n3. Type <Return> to fit (linear) uniform association model, ",
"\n using Diag() to fit diagonal effects: ")
readline()
}
else
message("2. Fit (linear) uniform association model, using Diag() to fit",
" diagonal effects")
}
Rscore <- scale(as.numeric(row(occupationalStatus)), scale = FALSE)
Cscore <- scale(as.numeric(col(occupationalStatus)), scale = FALSE)
Uniform <- gnm(Freq ~ origin + destination + Diag(origin, destination) +
Rscore:Cscore, family = poisson, data = occupationalStatus)
summary(Uniform)
{
if (interactive()) {
cat("\n3. Type <Return> to fit an association model using Mult() to fit",
"\n separate row and column effects:")
readline()
}
else message("3. Fit an association model using Mult() to fit separate row and ",
"column effects")
}
RC <- gnm(Freq ~ origin + destination + Diag(origin, destination) +
Mult(origin, destination), family = poisson,
data = occupationalStatus)
summary(RC)
{
if (interactive()) {
cat("\n4. Type <Return> to fit an association model using MultHomog()",
"\n to fit homogeneous row-column effects:")
readline()
}
else message("4. Fit an association model using MultHomog()\n",
"to fit homogeneous row-column effects")
}
RChomog <- gnm(Freq ~ origin + destination + Diag(origin, destination) +
MultHomog(origin, destination), family = poisson,
data = occupationalStatus)
summary(RChomog)
{
if (interactive()) {
cat("\n5. Type <Return> to compare models using anova:")
readline()
}
else message("5. Compare models using anova")
}
anova(Uniform, RChomog, RC)
message("6. Produce diagnostic plots for RChomog")
plot(RChomog)
message("7. Get simple constrasts of homogeneous row-column effects")
getContrasts(RChomog, grep("MultHomog", names(coef(RChomog))))
message("End of demo. \n",
"See vignette(\"gnmOverview\", package = \"gnm\") for full manual.")
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