# ~~ Methods for Function `merge` in Package `base` ~~ It allows to merge `momentModel` classes into system objects. methods ```r ## S4 method for signature 'linearModel,linearModel' merge(x, y, ...) ## S4 method for signature 'nonlinearModel,nonlinearModel' merge(x, y, ...) ## S4 method for signature 'slinearModel,linearModel' merge(x, y, ...) ## S4 method for signature 'snonlinearModel,nonlinearModel' merge(x, y, ...) ``` ## Arguments - `x`: An object on which the other objects are merged to. - `y`: An object to be merged to `x`. - ``...``: Other objects of the same class as `y` to be merged to `x`. ## Methods - **`signature(x = "linearModel", y = "linearModel")`**: Merging linear models into a system of equations. - **`signature(x = "nonlinearModel", y = "nonlinearModel")`**: Merging nonlinear models into a system of equations. - **`signature(x = "slinearModel", y = "linearModel")`**: Adding linear equations to a system of linear equations. - **`signature(x = "snonlinearModel", y = "nonlinearModel")`**: Adding nonlinear equations to a system of nonlinear equations. ## Examples ```r data(simData) g1 <- y1~x1+x4; h1 <- ~z1+z2+z3+z4+x4 g2 <- y2~x1+x2+x3; h2 <- ~z1+z2+z3+z4+x3 g3 <- y3~x2+x3+x4; h3 <- ~z2+z3+z4+x3+x4 ## Linear models m1 <- momentModel(g1, h1, data=simData) m2 <- momentModel(g2, h2, data=simData) m3 <- momentModel(g3, h3, data=simData) ## (sys1 <- merge(m1, m2)) ## add an equation to the model (sys2 <- merge(sys1, m3)) ## want to get back the first? sys2[1:2] ## Nonlinear (not really, just written as nonlinear) nlg <- list(y1~theta0+theta1*x1+theta2*x4, y2~alpha0+alpha1*x1+alpha2*x2+alpha3*x3, y3~beta0+beta1*x2+beta2*x3+beta3*x4) theta0 <- list(c(theta0=1,theta1=2,theta2=3), c(alpha0=1,alpha1=2,alpha2=3, alpha3=4), c(beta0=1,beta1=2,beta2=3,beta3=4)) nm1 <- momentModel(nlg[[1]], h1, theta0[[1]], data=simData) nm2 <- momentModel(nlg[[2]], h2, theta0[[2]], data=simData) nm3 <- momentModel(nlg[[3]], h3, theta0[[3]], data=simData) merge(nm1, nm2, nm3) ```

merge-methods function