View source: R/pdynmc_fitMethods.R
fitted.pdynmc | R Documentation |
fitted.pdynmc
extracts fitted values of an object of class
'pdynmc'.
## S3 method for class 'pdynmc'
fitted(object, step = object$iter, na.rm = FALSE, ...)
object |
An object of class 'pdynmc'. |
step |
An integer denoting the iteration step for which fitted values are extracted (defaults to last iteration step used for obtaining parameter estimates). |
na.rm |
A logical variable indicating whether missing values should be removed from the vector of fitted values (defaults to 'FALSE'). |
... |
further arguments. |
Extract fitted values from object of class '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")
fitted(m1, na.rm = TRUE)
## Load data
data(ABdata, package = "pdynmc")
dat <- ABdata
dat[,c(4:7)] <- log(dat[,c(4:7)])
## Further 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")
fitted(m1, na.rm = TRUE)
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