From 1b0467540ac2bb92157927688fd5fed09ec5e819 Mon Sep 17 00:00:00 2001
From: Walmes Zeviani <walmes@ufpr.br>
Date: Wed, 25 Oct 2017 20:22:51 -0200
Subject: [PATCH] =?UTF-8?q?Atualiza=20script=20com=20c=C3=B3digo=20de=20sa?=
 =?UTF-8?q?la=20de=20aula.?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 scripts/ce089-06.R | 41 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 41 insertions(+)

diff --git a/scripts/ce089-06.R b/scripts/ce089-06.R
index 3107a37..533c3be 100644
--- a/scripts/ce089-06.R
+++ b/scripts/ce089-06.R
@@ -286,6 +286,8 @@ with(simul_model(),
          plot(y ~ x)
      })
 
+plot(y ~ x, data = simul_model())
+
 #--------------------------------------------
 # 2. Para cada novo conjunto de dados, obter os IC com cada método
 # usando um R = 999.
@@ -310,6 +312,7 @@ btst <- boot(data = simul_model(beta = beta),
 bci <- boot.ci(btst,
                type = "all",
                index = c(2, 2))
+bci
 str(bci)
 
 # Extração dos limites do IC.
@@ -336,7 +339,45 @@ apply(ics,
 #--------------------------------------------
 # 3. Repetir isso 100 vezes.
 
+proc <- function(..., R = 999) {
+    btst <- boot(data = simul_model(...),
+                 statistic = fitmodel,
+                 R = R)
+    bci <- boot.ci(btst,
+                   type = "all",
+                   index = c(2, 2))
+    ics <- sapply(bci[-(1:3)],
+                  FUN = function(x) {
+                      x[, ncol(x) - 1:0]
+                  })
+    inside <- apply(ics,
+                    MARGIN = 2,
+                    FUN = function(lim) {
+                        prod(lim - beta[2]) < 0
+                    })
+    return(inside)
+}
+
+system.time(proc(beta = c(-0.5, 1),
+                 x = rep(seq(0, 3, by = 0.5), 3),
+                 n = 21))
+
+N <- 5
+result <- replicate(N,
+                    proc(beta = c(-0.5, 1),
+                         x = rep(seq(0, 3, by = 0.5), 3),
+                         n = 21))
+
+str(result)
+# result
+
 #--------------------------------------------
 # 4. Verificar a taxa de cobertura dos intervalos de confiança.
 
+# apply()
+rowSums(result)/N
+
+# Salva imagem com os objetos criados.
+save.image(file = "my_results.RData")
+
 #-----------------------------------------------------------------------
-- 
GitLab