ndvuong.R
In micsr: Microeconometrics with R

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library(micsr)
Vuong <- vuong_sim(N = 100, R = 1000, Kf = 15, Kg = 1, a = 0.5)
head(Vuong)
mean(Vuong)
mean(abs(Vuong) > 1.96)

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library("ggplot2")
ggplot(data = data.frame(Vuong = Vuong)) + geom_density(aes(x = Vuong)) +
    geom_function(fun = dnorm, linetype = "dotted")

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library("micsr")
test <- ndvuong(turnout$group, turnout$intens, size = 0.05, pval = FALSE)
test

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ndvuong(turnout$group, turnout$intens, nd = FALSE)

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test <- ndvuong(turnout$group, turnout$intens, pval = TRUE)
test

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library("mlogit")
data("ModeCanada")
MC <- mlogit.data(ModeCanada, subset = noalt == 4, chid.var = "case",
                  alt.var = "alt", drop.index = TRUE)

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ml <- mlogit(choice ~ freq + cost + ivt + ovt | urban + income, MC, 
             reflevel = 'car', alt.subset = c("car", "train", "air"))

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hl <- mlogit(choice ~ freq + cost + ivt + ovt | urban + income, MC, 
             reflevel = 'car', alt.subset = c("car", "train", "air"),
             heterosc = TRUE)
coef(summary(hl))

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lmtest::waldtest(hl, heterosc = FALSE)
scoretest(ml, heterosc = TRUE)
lmtest::lrtest(hl, ml)

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ndvuong(hl, ml, nested = TRUE)

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library("mlogit")
data("RiskyTransport")
RT <- mlogit.data(RiskyTransport, shape = "long", choice = "choice",
                  chid.var = "chid", alt.var = "mode", id.var = "id")

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ml <- mlogit(choice ~ cost, data = RT)
hl <- mlogit(choice ~ cost , data = RT, heterosc = TRUE)
nl <- mlogit(formula = choice ~ cost, data = RT,
             nests = list(fast = c("Helicopter", "Hovercraft"),
                          slow = c("WaterTaxi", "Ferry")),
             un.nest.el = TRUE)
modelsummary::msummary(list(multinomial = ml, heteroscedastic = hl, nested =  nl))

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ndvuong(nl, hl, vartest = TRUE)

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ndvuong(hl, nl)