NLSUR

nlsur is a package to estimate a nonlinear least squares for single equations or systems of equations. The function to interact with is nlsur(). This function can estimate Nonlinear-Least Squares (NLS), Feasible Generalized NLS (FGNLS) and Iterative FGNLS (IFGNLS).

The packages supports a variety of functions like print(), coef(), summary(), logLik(), vcov() and predict().

Installation

Via r-universe:

install.packages("nlsur", repos = c("https://janmarvin.r-universe.dev", "https://cloud.r-project.org"))

Via devtools:

devtools::install_github("JanMarvin/nlsur")

Application

With nlsur() it is rather straight forward to estimate nonlinear demand systems. As example the following Translog demand system can be estimated.

data(costs)

dat <- costs
# apply a patch to create Greene Ed. 7 Data
dat$Sm[dat$Year == 1958] <- 0.61886
dat$Pe[dat$Year == 1950] <- 1.12442
dat$Pm[dat$Year == 1949] <- 1.06625

# model
model <- list(
  Sk ~ bk + dkk * log(Pk/Pm) + dkl * log(Pl/Pm) + dke * log(Pe/Pm),
  Sl ~ bl + dkl * log(Pk/Pm) + dll * log(Pl/Pm) + dle * log(Pe/Pm),
  Se ~ be + dke * log(Pk/Pm) + dle * log(Pl/Pm) + dee * log(Pe/Pm)
)

erg <- nlsur(eqns = model, data = dat, type = "FGNLS")
erg

Additional parameters may be obtained using nlcom() a wrapper for the delta method.

# indirect estimation of translog parameters
bm  <- nlcom(object = erg, form = "1 -be -bk -bl",  rname = "bm")
dkm <- nlcom(object = erg, form = "-dkk -dkl -dke", rname = "dkm")
dlm <- nlcom(object = erg, form = "-dkl -dll -dle", rname = "dlm")
dem <- nlcom(object = erg, form = "-dke -dle -dee", rname = "dem")

# and now dmm (nlcom can search for parameters)
dmm <- nlcom(object = erg, form = "-dkm -dlm -dem", rname = "dmm")