library(ggplot2)
library(data.table)
library(SFAt)
library(SFAsim)
library(lmtest)
library(plm)
# CROSS-SECTION DATA ------------------------------------------------------
test_data_cs <- sim_data_cs(N = 1000, frontier_sigma = 1, z_coef = c(1, -0.3, 0.1))
colnames(test_data_cs)
ggplot(data = as.data.frame(test_data_cs),
aes(x = a_2,
y = log(y)))+
geom_point() +
# facet_wrap(~group, ncol = , scales = "free") +
theme(legend.position = "bottom") +
ggtitle("title")
SFA(y ~ a_1 + a_2 + b_1_1 + b_1_2 + b_2_2,
cm = ~ z1 + z2,
# dist = "exp",
data = as.data.frame(test_data_cs))
lrtest(.Last.value)
# PANEL DATA --------------------------------------------------------------
test_data <- as.data.table(sim_data_panel(k = 30,
x_coef = c(8, 2, -1),
z_sd = 0.5,
z_intercept = 0.5,
z_coef = c(1, -0.5),
sigma_v = 1,
sigma_u = 1))
ggplot(data = melt(test_data, id.vars = c("k", "t")),
aes(x = t,
y = value,
color = as.factor(k))) +
geom_line() +
facet_wrap(~variable, ncol = , scales = "free") +
theme(legend.position = "bottom") +
ggtitle("title")
hist(test_data$eps)
# test_data$
fit <- SFA(y ~ x1 + x2,
# dist = "tnorm",
data = test_data)
print(fit)
lrtest(fit)
ineff_fit <- inefficiencyTerm(fit, "JLMS")
plot(test_data$u ~ ineff_fit)
cor(test_data$u, ineff_fit)
summary(plm(ineff_fit ~ z1 + z2, index = c("k", "t"), data = test_data))
fit_cm <- SFA(y ~ x1 + x2,
data = test_data,
dist = "tnorm",
grad = "analytic",
cm = ~ as.factor(k) + z1 + z2,
optim_control = list(trace = 1, maxit = 1000))
print(fit_cm)
lrtest(fit_cm)
ineff_fit_cm <- inefficiencyTerm(fit_cm, "BC")
plot(test_data$u ~ ineff_fit_cm)
cor(test_data$u, ineff_fit_cm)
cor(ineff_fit, ineff_fit_cm, use = "pairwise.complete.obs")
# library(frontier)
# fit_front <- frontier::sfa(y ~ x1 + x2 | z1 + z2,
# data = test_data, maxit = 20)
# summary(fit_front)
# cor(test_data$u, log(1/efficiencies(fit_front)))
# PANEL DATA WITH AR ------------------------------------------------------
test_data <- as.data.table(sim_data_panel_ar(k = 20,
x_coef = c(8, 2, -1),
z_sd = 0.5,
# z_intercept = 0.5,
z_coef = c(1, -0.5),
sigma_v = 1,
sigma_u = 1,
dist = "gamma"))
ggplot(data = melt(test_data, id.vars = c("k", "t")),
aes(x = t,
y = value,
color = as.factor(k))) +
geom_line() +
facet_wrap(~variable, ncol = , scales = "free") +
theme(legend.position = "bottom") +
ggtitle("title")
hist(test_data$eps)
# test_data$
fit <- SFA(y ~ x1 + x2,
data = test_data)
print(fit)
lrtest(fit)
ineff_fit <- inefficiencyTerm(fit, "JLMS")
plot(test_data$u ~ ineff_fit)
cor(test_data$u, ineff_fit)
summary(plm(ineff_fit ~ cumsum(z1) + cumsum(z2), data = test_data, index = c("k", "t")))
fit_cm <- SFA(y ~ x1 + x2,
data = test_data,
dist = "tnorm",
cm = ~ as.factor(k) + cumsum(z1) + cumsum(z2),
optim_control = list(trace = 1))
print(fit_cm)
lrtest(fit_cm)
ineff_fit_cm <- inefficiencyTerm(fit_cm, "JLMS")
plot(test_data$u ~ ineff_fit_cm)
cor(test_data$u, ineff_fit_cm)
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