# Summary method for Laplace Approximation objects Summary method for objects of class `laplace`. Similar to the method for objects of class `aghq`, but assumes the problem is high-dimensional and does not compute or print any large objects or summaries. See `summary.aghq` for further information. ```r ## S3 method for class 'laplace' summary(object, ...) ``` ## Arguments - `object`: An object of class `laplace`. - `...`: not used. ## Returns Silently prints summary information. ## Examples ```r logfteta2d <- function(eta,y) { # eta is now (eta1,eta2) # y is now (y1,y2) n <- length(y) n1 <- ceiling(n/2) n2 <- floor(n/2) y1 <- y[1:n1] y2 <- y[(n1+1):(n1+n2)] eta1 <- eta[1] eta2 <- eta[2] sum(y1) * eta1 - (length(y1) + 1) * exp(eta1) - sum(lgamma(y1+1)) + eta1 + sum(y2) * eta2 - (length(y2) + 1) * exp(eta2) - sum(lgamma(y2+1)) + eta2 } set.seed(84343124) n1 <- 5 n2 <- 5 n <- n1+n2 y1 <- rpois(n1,5) y2 <- rpois(n2,5) objfunc2d <- function(x) logfteta2d(x,c(y1,y2)) funlist2d <- list( fn = objfunc2d, gr = function(x) numDeriv::grad(objfunc2d,x), he = function(x) numDeriv::hessian(objfunc2d,x) ) thelaplace <- laplace_approximation(funlist2d,c(0,0)) # Summarize and automatically call its print() method when called interactively: summary(thelaplace) ``` ## See Also Other quadrature: `aghq()`, `get_hessian()`, `get_log_normconst()`, `get_mode()`, `get_nodesandweights()`, `get_numquadpoints()`, `get_opt_results()`, `get_param_dim()`, `laplace_approximation()`, `marginal_laplace_tmb()`, `marginal_laplace()`, `nested_quadrature()`, `normalize_logpost()`, `optimize_theta()`, `plot.aghq()`, `print.aghqsummary()`, `print.aghq()`, `print.laplacesummary()`, `print.laplace()`, `print.marginallaplacesummary()`, `summary.aghq()`, `summary.marginallaplace()` Other quadrature: `aghq()`, `get_hessian()`, `get_log_normconst()`, `get_mode()`, `get_nodesandweights()`, `get_numquadpoints()`, `get_opt_results()`, `get_param_dim()`, `laplace_approximation()`, `marginal_laplace_tmb()`, `marginal_laplace()`, `nested_quadrature()`, `normalize_logpost()`, `optimize_theta()`, `plot.aghq()`, `print.aghqsummary()`, `print.aghq()`, `print.laplacesummary()`, `print.laplace()`, `print.marginallaplacesummary()`, `summary.aghq()`, `summary.marginallaplace()`

summary.laplace function