getRestrict-methods: Methods for Function 'getRestrict' in Package 'gmm4'
In gmm4: S4 Generalized Method of Moments

Description Usage Arguments Methods Examples

It computes the matrices related to linear and nonlinear contraints. Those matrices are used to perform hypothesis tests.

## 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 `gmmModels`, `rGmmModels`, and `rsysGmmModels`.
`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 `restModel` for more details.
`rhs`	The right hand side for the restriction on the coefficients. See `restModel` for more details. It is ignored for objects of class `"nonlinearGmm"`.

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.

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$R-rest$q
v <- rest$dR%*%vcov(res)%*%t(rest$dR)
(test <- crossprod(g, solve(v, g)))
(pv <- 1-pchisq(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$R-rest$q
v <- rest$dR%*%vcov(res)%*%t(rest$dR)
(test <- crossprod(g, solve(v, g)))
(pv <- 1-pchisq(test, length(rest$R)))

## See hypothesisTest method for an easier approach.