# Simulate a glarma process. Simulate a single instance of a glarma process specified by an object of class `glarmaSim`. ```r glarmaSim(object) ``` ## Arguments - `object`: An object of class "glarmaSim" either constructed to be of that class or derived from a fitted glarma model using the function `extractGlarmaSimModel`. ## Returns An object of class `"glarmaSimulation"`. ## Author(s) "William T.M. Dunsmuir" and "David J Scott" ## See Also `glarmaSim` ## Examples ```r ### Polio data data("Polio") y <- Polio[, 2] X <- as.matrix(Polio[, 3:8]) glarmamod <- glarma(y, X, thetaLags = c(1,2,5), type = "Poi", method = "FS", residuals = "Pearson", maxit = 100, grad = 1e-6) PolioModel <- extractGlarmaSimModel(glarmamod) str(PolioModel) par(mfrow = c(3,1)) sim <- glarmaSim(PolioModel) ts.plot(sim$W) ts.plot(sim$mu) ts.plot(sim$Y) ### Example with Oxford-Cambridge Boat Race data(OxBoatRace) y1 <- OxBoatRace$Camwin n1 <- rep(1, length(OxBoatRace$Year)) Y <- cbind(y1, n1 - y1) X <- cbind(OxBoatRace$Intercept, OxBoatRace$Diff) colnames(X) <- c("Intercept", "Weight Diff") oxcamglm <- glm(Y ~ Diff + I(Diff^2), data = OxBoatRace, family = binomial(link = "logit"), x = TRUE) summary(oxcamglm) X <- oxcamglm$x glarmamod <- glarma(Y, X, thetaLags = c(1, 2), type = "Bin", method = "NR", residuals = "Pearson", maxit = 100, grad = 1e-6) str(glarmamod) BoatRaceModel <- glarmaSimModel(X, beta = coef.glarma(glarmamod, type = "beta"), phiLags = glarmamod$phiLags, phi = rep(0.1, length(glarmamod$phiLags)), thetaLags = glarmamod$thetaLags, theta = c(0.34,0.56), type = glarmamod$type, m = n1, residType = glarmamod$residType) str(BoatRaceModel) BoatRaceModel <- extractGlarmaSimModel(glarmamod) str(BoatRaceModel) par(mfrow = c(3,1)) sim <- glarmaSim(BoatRaceModel) ts.plot(sim$W) ts.plot(sim$mu) ts.plot(sim$Y) ### Example with asthma data, negative binomial data(Asthma) y <- Asthma[, 1] X <- as.matrix(Asthma[, 2:16]) ## Pearson Residuals, Newton Raphson, Negative Binomial ## Initial value of the shape parameter take to be zero glarmamod <- glarma(y, X, thetaLags = 7, type = "NegBin", method = "NR", residuals = "Pearson", alphaInit = 0, maxit = 100, grad = 1e-6) summary(glarmamod) str(glarmamod) AsthmaModel <- glarmaSimModel(X, beta = coef.glarma(glarmamod, type = "beta"), phiLags = glarmamod$phiLags, phi = rep(0.1, length(glarmamod$phiLags)), thetaLags = glarmamod$thetaLags, theta = c(0.044), type = glarmamod$type, alpha = 37.19, residType = glarmamod$residType) str(AsthmaModel) AsthmaModel <- extractGlarmaSimModel(glarmamod) str(AsthmaModel) par(mfrow = c(3,1)) sim <- glarmaSim(AsthmaModel) ts.plot(sim$W) ts.plot(sim$mu) ts.plot(sim$Y) ```

glarmaSim function