clusterEst: Calculate coefficients and covariance with clusting standard...

In LiangCZhang/Rcess: Rcess: An R package for calculating estimates of costs and economies of scale and scope

Description

Calculate coefficients and covariance with clusting standard deviations

Usage

clusterEst(model, dfcw = 1, cluster)

Arguments

model	The estimated model(nls class object).
cluster	A vector, matrix, or data.frame of cluster variables, where each column is a separate variable.

Value

An list of estimation results and clustering variance

Author(s)

Liang-Cheng Zhang

References

Arai, M. (2015). Cluster-robust standard errors using R.
Retrieved from http://www.ne.su.se/polopoly_fs/1.216115.1426234213!/menu/standard/file/clustering1.pdf

Petersen, M. A. (2009). Estimating standard errors in finance panel data sets: Comparing approaches. Review of Financial Studies, 22(1), 435-480.

Examples

##Simple example
data(unidat)
m1 = nls(c ~ b0+b1*y1,start=list(b0=1,b1=0), data = unidat)
cluster.vcov(m2, petersen$firmid)

##Reproduce results of Table 4 in Zhang et al. (in press)
data(unidat)
library(minpack.lm)
model <- nlsLM(costFunction(costName = colnames(unidat)[3], outputName =
colnames(unidat)[7:11], priceName = colnames(unidat)[4:6], controlName =
 colnames(unidat)[12:24], form = "FFCQ-M"), start = list(b0 = 600,
 b1 = 0, b2 = 0, b3 = 0, b4 = 0, b5 = 0, b11 = 0, b22 = 0, b33 = 0, b44 = 0,
 b55 = 0, b12 = 0, b13 = 0, b14 = 0, b15 = 0, b23 = 0, b24 = 0,
 b25 = 0, b34 = 0, b35 = 0, b45 = 0, bp2 = 0, bp3 = 0, bz1 = 0,
 bz2 = 0, bz3 = 0, bz4 = 0, bz5 = 0, bz6 = 0, bz7 = 0, bz8 = 0,
 bz9 = 0, bz10 = 0, bz11 = 0, bz12 = 0, bz13 = 0), data = unidat,
 trace = F)
clusterEst(model = model , cluster = unidat$unicode)$model #extract summary results
clusterEst(model = model , cluster = unidat$unicode)$vcovCL #extract covariance

LiangCZhang/Rcess documentation built on May 8, 2019, 8:52 p.m.