# Parameter Generators Functions which use the arguments of a `glarma` call to generate the initial `delta`, `theta` and `phi` vectors. ```r deltaGen(y, X, offset = NULL, phiInit, thetaInit, type, alpha, beta, alphaInit) thetaGen(thetaLags, thetaInit) phiGen(phiLags, phiInit) ``` ## Arguments - `y`: Numeric vector; response variable. - `X`: Matrix; the explanatory variables. A vector of ones should be added to the data matrix as the first column for the `beta` of the intercept. - `offset`: Either `NULL` or a numeric vector of length equal to the number of cases. Used to specify an **a priori** known component to be included in the linear predictor during fitting. - `phiInit`: Numeric vector; initial values for the corresponding AR orders. - `thetaInit`: Numeric vector; initial values for the corresponding orders. - `type`: Character; the count distribution. The default is the Poisson distribution. - `beta`: Numeric vector; initial values of the parameters of variables. It is for the user to construct the specific `delta` by themselves. - `alpha`: Numeric; an optional initial `theta` parameter for `glm.nb`. - `alphaInit`: Numeric; an initial `theta` parameter for `glarma` for negative binomial counts. - `thetaLags`: Numeric vector; MA orders - `phiLags`: Numeric vector; AR orders ## Details The `thetaGen` and `phiGen` functions take the arguments, `thetaLags`, `phiLags`, `thetaInit` and `phiInit`, in a `glarma` call to generate and return the initial `theta` and `phi` vectors with orders corresponding to their names. Then the `deltaGen` function uses the values returned by `thetaGen`, `phiGen` and other arguments in the `glarma` call to generate and return the initial `delta` vector with correct names. ## Returns `thetaGen` returns a list containing `thetaLags` and `thetaInit`. `thetaInit` is the initial `theta` vector with its corresponding MA orders as its names. `phiGen` returns a list containing `phiLags` and `phiInit`. `phiInit` is the initial `phi` vector with its corresponding MA orders as its names. `deltaGen` returns a named vector giving the values of `beta`, `phiInit`, `thetaInit` plus `alpha` in the negative binomial case. ## Author(s) "Cenanning Li" and "William T.M. Dunsmuir" ## Examples ```r ### Using the polio data data(Polio) y <- Polio[, 2] X <- as.matrix(Polio[, 3:8]) ## generate the theta vector theta.lags <- c(1, 2, 5) theta.init <- c(0.0, 0.0, 0.0) theta <- thetaGen(theta.lags, theta.init) print(thetaLags <- theta[[1]]) print(theta.init <- theta[[2]]) ## generate the vector of phi phi.lags <- rep(0, 0) phi.init <- rep(0, 0) phi <- phiGen(phi.lags, phi.init) print(phiLags <- phi[[1]]) print(phi.init <- phi[[2]]) ## generate the delta vector delta <- deltaGen(y = y, X = X, phiInit = phi.init, thetaInit = theta.init, type = "Poi", alpha = 1) delta ```

paramGen function