subsetting: Subsetting methods
In gmm4: S4 Generalized Method of Moments

Description Methods Examples

Different subsetting methods for S4 class objects of the package. The subset method returns an new object with observations selected by the second argument. See example.

signature(x = "gmmWeights", i = "integer", j = "missing"): It creates a partition from the weighting matrix.
signature(x = "gmmWeights", i = "missing", j = "missing"): It generates the whole weighting matrix.
signature(x = "sysGmmWeights", i = "missing", j = "list"): It creates a partition from the weighting matrix. j has no effect here. It creates a partition from the weighting matrix in a systemof equations. i selects the equation and the list j the moments in each equation. Missing i means all equations.
signature(x = "sysGmmWeights", i = "numeric", j = "missing"): It creates a partition from the weighting matrix. j has no effect here. It creates a partition from the weighting matrix in a systemof equations. i selects the equation and the list j the moments in each equation. Missing j means all moments.
signature(x = "sysGmmWeights", i = "missing", j = "missing"): No effect. It returns x.
signature(x = "snonlinearGmm", i = "numeric", j="missing"): It generates a system of equations with a subset of equations selected by i. If the number of remaining equations is one, it returns an object of class "nonlinearGmm".
signature(x = "slinearGmm", i = "numeric", j="missing"): It generates a system of equations with a subset of equations selected by i. If the number of remaining equations is one, it returns an object of class "linearGmm".
signature(x = "rslinearGmm", i = "numeric", j="missing"): It is only use to select one equation when no cross-equation restrictions are imposed. Only one equation can be selected.
signature(x = "sysGmmModels", i = "numeric", j="list"): It generates a system of equations with a subset of equations selected by i and a subset of moment conditions selected by j. If the number of remaining equations is one, it returns an object of class "linearGmm".
signature(x = "sysGmmModels", i = "missing", j="missing"): No effect. It returns x.
signature(x = "gmmModels", i = "missing", j = "missing"): Returns the model without any change.
signature(x = "functionGmm", i = "numeric", j = "missing"): It generates the same model with a subset of the moment conditions.
signature(x = "formulaGmm", i = "numeric", j = "missing"): It generates the same model with a subset of the moment conditions.
signature(x = "rfuncionGmm", i = "numeric", j = "missing"): It generates the same model with a subset of the moment conditions. j has no effect here.

set.seed(1122)
x1 <- rchisq(50,5)
x2 <- rchisq(50,5)
x3 <- rnorm(50)
z1 <- .2*x1+rnorm(50)
z2 <- rnorm(50)
z3 <- rnorm(50)
y <- x1+rnorm(50)
dat <- data.frame(y=y,z1=z1,x1=x1,z2=z2,x2=x2,z3=z3,x3=x3)
model1 <- gmmModel(y~x1+x2, ~x2+x3+z1+z2+z3, data=dat, vcov="MDS")
w <- evalWeights(model1, theta=1:3)
w[]
w[1:3]

## A model with a subset of the instruments
model1[1:4]

## Selecting the observations:

subset(model1, x1<3)
subset(model1, 1:25)