Description Usage Arguments Methods Examples
It computes the matrices related to linear and nonlinear contraints. Those matrices are used to perform hypothesis tests.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26  ## S4 method for signature 'rlinearGmm'
getRestrict(object, theta)
## S4 method for signature 'rslinearGmm'
getRestrict(object, theta)
## S4 method for signature 'rnonlinearGmm'
getRestrict(object, theta)
## S4 method for signature 'rformulaGmm'
getRestrict(object, theta)
## S4 method for signature 'gmmModels'
getRestrict(object, theta, R, rhs=NULL)
## S4 method for signature 'gelModels'
getRestrict(object, theta, R, rhs=NULL)
## S4 method for signature 'sysGmmModels'
getRestrict(object, theta, R, rhs=NULL)
## S4 method for signature 'rfunctionGmm'
getRestrict(object, theta)
## S4 method for signature 'rgelModels'
getRestrict(object, theta)

object 
Object of class included in 
theta 
A vector of coefficients for the unrestricted model (see examples). 
R 
A matrix, character or list of formulas that specifies the
contraints to impose on the coefficients. See

rhs 
The right hand side for the restriction on the
coefficients. See 
signature(object = "gmmModels")
A restricted model is created from the constraints, and the restriction matrices are returned. The methods is applied to linear and nonlinear models in a regression form.
signature(object = "gelModels")
A restricted model is created from the constraints, and the restriction matrices are returned. The methods is applied to linear and nonlinear models in a regression form.
signature(object = "rgelModels")
The restriction matrices are evaluated at the coefficient vector
theta
of the unrestricted representation.
signature(object = "sysGmmModels")
A restricted model is created from the constraints, and the restriction matrices are returned. The methods is applied to systems of linear and nonlinear models.
signature(object = "rlinearGmm")
The restriction matrices are evaluated at the coefficient vector
theta
of the unrestricted representation.
signature(object = "rslinearGmm")
The restriction matrices are evaluated at the coefficient vector
theta
of the unrestricted representation.
signature(object = "rnonlinearGmm")
The restriction matrices are evaluated at the coefficient vector
theta
of the unrestricted representation.
signature(object = "rfunctionGmm")
The restriction matrices are evaluated at the coefficient vector
theta
of the unrestricted representation.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32  data(simData)
theta < c(beta0=1,beta1=2)
## Unrestricted model
model1 < gmmModel(y~x1+x2+x3+z1, ~x1+x2+z1+z2+z3+z4, data=simData)
## The restricted model
R1 < c("x1","2*x2+z1=2", "4+x3*5=3")
res < modelFit(model1)
rest < getRestrict(model1, coef(res), R1)
## it allows to test the restriction
g < rest$Rrest$q
v < rest$dR%*%vcov(res)%*%t(rest$dR)
(test < crossprod(g, solve(v, g)))
(pv < 1pchisq(test, length(rest$R)))
## Delta Method:
## To impose nonlinear restrictions, we need to convert
## the linear model into a nonlinear one
NLmodel < as(model1, "nonlinearGmm")
R1 < c("theta2=2", "theta3=theta4^2")
res < modelFit(NLmodel)
rest < getRestrict(NLmodel, coef(res), R1)
g < rest$Rrest$q
v < rest$dR%*%vcov(res)%*%t(rest$dR)
(test < crossprod(g, solve(v, g)))
(pv < 1pchisq(test, length(rest$R)))
## See hypothesisTest method for an easier approach.

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