R Under development (unstable) (2024-04-23 r86473 ucrt) -- "Unsuffered Consequences"
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> library(epigrowthfit)
> options(warn = 2L, error = if (interactive()) recover)
> 
> .S3method("split", "formula",
+           function(x, f, drop = FALSE, ...) {
+           	l <- epigrowthfit:::split_effects(x)
+           	`attr<-`(l[[1L]], "random", l[-1L])
+           })
> 
> o.1 <- egf_cache("egf-1.rds")
> o.2 <- egf_cache("egf-2.rds")
> 
> 
> ## fixef ###############################################################
> 
> o.2c <- coef(o.2, random = TRUE, full = TRUE)
> o.2f <- fixef(o.2)
> o.2f.e <- data.frame(bottom = epigrowthfit:::disambiguate(rep.int("beta", 2L)),
+                      top = gl(2L, 1L, labels = c("log(r)", "log(c0)")),
+                      term = gl(1L, 2L, labels = "(Intercept)"),
+                      colname = rep.int("(Intercept)", 2L),
+                      value = o.2c[1:2])
> stopifnot(identical(o.2f, o.2f.e))
> 
> 
> ## ranef ###############################################################
> 
> o.2c <- coef(o.2, random = TRUE, full = TRUE)
> o.2r <- ranef(o.2, makeSigma = TRUE)
> 
> o.2r.e <- data.frame(cov = gl(1L, 40L, labels = epigrowthfit:::disambiguate("Sigma")),
+                      vec = gl(20L, 2L, labels = epigrowthfit:::disambiguate(rep.int("u", 20L))),
+                      bottom = epigrowthfit:::disambiguate(rep.int("b", 40L)),
+                      top = gl(2L, 1L, 40L, labels = c("log(r)", "log(c0)")),
+                      term = gl(1L, 40L, labels = "(Intercept)"),
+                      group = gl(1L, 40L, labels = "country:wave"),
+                      level = gl(20L, 2L, labels = paste0(gl(10L, 1L, 20L, labels = LETTERS[1:10]), ":", gl(2L, 10L))),
+                      colname = sprintf("((Intercept) | country%s:wave%s)", gl(10L, 2L, 40L, labels = LETTERS[1:10]), gl(2L, 20L)),
+                      value = o.2c[-(1:5)])
> 
> Sigma <- list(theta2cov(o.2c[3:5]))
> names(Sigma) <- levels(o.2r[["cov"]])
> dimnames(Sigma[[1L]])[1:2] <- list(levels(o.2r[["top"]]))
> attr(o.2r.e, "Sigma") <- Sigma
> 
> stopifnot(identical(o.2r, o.2r.e))
> 
> 
> ## vcov ################################################################
> 
> stopifnot(identical(vcov(o.1),
+                     o.1[["tmb_out"]][["env"]][[".__egf__."]][["adreport"]][["cov.fixed"]]))
> 
> 
> ## getCall #############################################################
> 
> o <- list(call = call("egf.method"))
> class(o) <- "egf"
> stopifnot(identical(getCall(o), call("egf")))
> class(o) <- "egf_no_fit"
> stopifnot(identical(getCall(o), call("egf")))
> 
> 
> ## model.frame #########################################################
> 
> mf0 <- model.frame(o.1, which = "ts", full = FALSE)
> mf1 <- model.frame(o.1, which = "ts", full = TRUE)
> mf2 <- model.frame(o.1, which = "windows")
> mf3 <- model.frame(o.1, which = "parameters", top = "log(r)")
> mf4 <- model.frame(o.1, which = "extra")
> mf5 <- model.frame(o.1, which = "combined")
> 
> frame <- o.1[["frame"]]
> 
> d5 <- do.call(cbind, unname(frame[["parameters"]]))
> d5 <- cbind(d5, frame[["extra"]])
> d5 <- d5[!duplicated(names(d5))]
> 
> stopifnot(exprs = {
+ 	identical(mf0, frame[["ts"]][!is.na(frame[["ts"]][["window"]]), , drop = FALSE])
+ 	identical(mf1, frame[["ts"]])
+ 	identical(mf2, frame[["windows"]])
+ 	identical(mf3, frame[["parameters"]][["log(r)"]])
+ 	identical(mf4, frame[["extra"]])
+ 	identical(mf5, d5)
+ })
> 
> 
> ## model.matrix ########################################################
> 
> X <- model.matrix(o.1, which =  "fixed")
> Z <- model.matrix(o.1, which = "random")
> 
> X1 <- model.matrix(o.1, which =  "fixed", top = "log(r)")
> Z1 <- model.matrix(o.1, which = "random", top = "log(r)")
> Z2 <- model.matrix(o.1, which = "random", top = "log(r)",
+                    random = quote(1 | country:wave))
> 
> o.1f <- fixef(o.1)
> o.1r <- ranef(o.1)
> 
> stopifnot(exprs = {
+ 	identical(X,
+ 	          structure(o.1[["tmb_out"]][["env"]][["data"]][["Xd"]],
+ 	                    contrasts = o.1[["contrasts"]][["X"]]))
+ 	identical(Z,
+ 	          structure(o.1[["tmb_out"]][["env"]][["data"]][["Z"]],
+ 	                    contrasts = o.1[["contrasts"]][["Z"]]))
+ 	identical(as.double(X1),
+ 	          as.double(X[, o.1f[["top"]] == "log(r)", drop = FALSE]))
+ 	identical(as.double(Z1),
+ 	          as.double(Z[, o.1r[["top"]] == "log(r)", drop = FALSE]))
+ 	identical(Z2, Z1)
+ })
> 
> 
> ## terms ###############################################################
> 
> stopifnot(identical(terms(o.1, top = "log(r)"),
+                     terms(model.frame(o.1, which = "parameters", top = "log(r)"))))
> 
> 
> ## formula #############################################################
> 
> o.1f.0 <- formula(o.1, top = "log(r)", split = FALSE)
> o.1f.1 <- formula(o.1, top = "log(r)", split = TRUE)
> stopifnot(exprs = {
+ 	identical(o.1f.0, formula(terms(o.1, top = "log(r)")))
+ 	identical(o.1f.1, split(o.1f.0))
+ })
> 
> 
> ## nobs ################################################################
> 
> x <- model.frame(o.1, which = "ts", full = FALSE)[["x"]]
> stopifnot(identical(nobs(o.1), sum(!is.na(x))))
> 
> 
> ## df.residual #########################################################
> 
> stopifnot(identical(df.residual(o.1),
+                     as.double(nobs(o.1)) - sum(!o.1[["random"]])))
> 
> 
> ## logLik ##############################################################
> 
> stopifnot(identical(logLik(o.1),
+                     structure(-o.1[["value"]],
+                               df = sum(!o.1[["random"]]),
+                               nobs = nobs(o.1),
+                               class = "logLik")))
> 
> 
> ## extractAIC ##########################################################
> 
> ll <- logLik(o.1)
> df <- attr(ll, "df")
> stopifnot(identical(extractAIC(o.1), c(df, -2 * as.double(ll) + 2 * df)))
> 
> proc.time()
   user  system elapsed 
   1.32    0.12    1.45