View source: R/pdynmc_fitMethods.R
print.summary.pdynmc | R Documentation |
print.summary.pdynmc
prints the summary for objects of class
'pdynmc'.
## S3 method for class 'summary.pdynmc'
print(
x,
digits = max(3, getOption("digits") - 3),
signif.stars = getOption("show.signif.stars"),
...
)
x |
An object of class 'summary.pdynmc'. |
digits |
An integer indicating the maximum number of digits to display in the object. |
signif.stars |
Argument is defined as in |
... |
further arguments. |
Print information on objects of class 'summary.pdynmc'.
Markus Fritsch
pdynmc
for fitting a linear dynamic panel data model.
## Load data
data(ABdata, package = "pdynmc")
dat <- ABdata
dat[,c(4:7)] <- log(dat[,c(4:7)])
dat <- dat[c(1:140), ]
## Code example
m1 <- pdynmc(dat = dat, varname.i = "firm", varname.t = "year",
use.mc.diff = TRUE, use.mc.lev = FALSE, use.mc.nonlin = FALSE,
include.y = TRUE, varname.y = "emp", lagTerms.y = 2,
fur.con = TRUE, fur.con.diff = TRUE, fur.con.lev = FALSE,
varname.reg.fur = c("wage", "capital", "output"), lagTerms.reg.fur = c(1,2,2),
include.dum = TRUE, dum.diff = TRUE, dum.lev = FALSE, varname.dum = "year",
w.mat = "iid.err", std.err = "corrected", estimation = "onestep",
opt.meth = "none")
summary(m1)
## Load data
data(ABdata, package = "pdynmc")
dat <- ABdata
dat[,c(4:7)] <- log(dat[,c(4:7)])
m1 <- pdynmc(dat = dat, varname.i = "firm", varname.t = "year",
use.mc.diff = TRUE, use.mc.lev = FALSE, use.mc.nonlin = FALSE,
include.y = TRUE, varname.y = "emp", lagTerms.y = 2,
fur.con = TRUE, fur.con.diff = TRUE, fur.con.lev = FALSE,
varname.reg.fur = c("wage", "capital", "output"), lagTerms.reg.fur = c(1,2,2),
include.dum = TRUE, dum.diff = TRUE, dum.lev = FALSE, varname.dum = "year",
w.mat = "iid.err", std.err = "corrected", estimation = "onestep",
opt.meth = "none")
summary(m1)
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