# Aster Model Simulation Random generation of data for Aster models. ```r raster(theta, pred, fam, root, famlist = fam.default()) ``` ## Arguments - `theta`: canonical parameter of the conditional model. A matrix, rows represent individuals and columns represent nodes in the graphical model. - `pred`: integer vector of length `ncol(theta)` determining the graph. `pred[j]` is the index of the predecessor of the node with index `j` unless the predecessor is a root node, in which case `pred[j] == 0`. - `fam`: integer vector of length `ncol(theta)` determining the exponential family structure of the aster model. Each element is an index into the vector of family specifications given by the argument `famlist`. - `root`: A matrix of the same dimensions as `theta`. Data `root[i, j]` is the data for the founder that is the predecessor of the `[i, j]` node. - `famlist`: a list of family specifications (see `families`). ## Returns A matrix of the same dimensions as `theta`. The random data for an aster model with the specified graph, parameters, and root data. ## Examples ```r ### see package vignette for explanation ### data(echinacea) vars <- c("ld02", "ld03", "ld04", "fl02", "fl03", "fl04", "hdct02", "hdct03", "hdct04") redata <- reshape(echinacea, varying = list(vars), direction = "long", timevar = "varb", times = as.factor(vars), v.names = "resp") redata <- data.frame(redata, root = 1) pred <- c(0, 1, 2, 1, 2, 3, 4, 5, 6) fam <- c(1, 1, 1, 1, 1, 1, 3, 3, 3) hdct <- grep("hdct", as.character(redata$varb)) hdct <- is.element(seq(along = redata$varb), hdct) redata <- data.frame(redata, hdct = as.integer(hdct)) aout4 <- aster(resp ~ varb + nsloc + ewloc + pop * hdct - pop, pred, fam, varb, id, root, data = redata) newdata <- data.frame(pop = levels(echinacea$pop)) for (v in vars) newdata[[v]] <- 1 newdata$root <- 1 newdata$ewloc <- 0 newdata$nsloc <- 0 renewdata <- reshape(newdata, varying = list(vars), direction = "long", timevar = "varb", times = as.factor(vars), v.names = "resp") hdct <- grep("hdct", as.character(renewdata$varb)) hdct <- is.element(seq(along = renewdata$varb), hdct) renewdata <- data.frame(renewdata, hdct = as.integer(hdct)) beta.hat <- aout4$coef theta.hat <- predict(aout4, model.type = "cond", parm.type = "canon") theta.hat <- matrix(theta.hat, nrow = nrow(aout4$x), ncol = ncol(aout4$x)) xstar <- raster(theta.hat, pred, fam, aout4$root) aout4star <- aster(xstar, aout4$root, pred, fam, aout4$modmat, beta.hat) beta.star <- aout4star$coef print(cbind(beta.hat, beta.star)) ``` ## See Also `aster`

raster function