From 2e20e79cd5496bb4048371e45fa7f6a8d72e4e08 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=90=D1=80=D1=82=D1=91=D0=BC=20=D0=A1=D0=B5=D1=80=D0=B5?=
 =?UTF-8?q?=D0=B1=D1=80=D1=8F=D0=BA=D0=BE=D0=B2?= <serebryak1234@bk.ru>
Date: Fri, 6 May 2022 20:58:25 +0000
Subject: [PATCH] Upload New File

---
 randproc21.R | 177 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 177 insertions(+)
 create mode 100644 randproc21.R

diff --git a/randproc21.R b/randproc21.R
new file mode 100644
index 0000000..5d7273e
--- /dev/null
+++ b/randproc21.R
@@ -0,0 +1,177 @@
+set.seed(3008)
+library(ggplot2)
+
+
+Tt = 10
+H = 0.05
+N = 100
+
+n = Tt/H
+n
+
+kh = seq(0,Tt,H)
+head(kh)
+tail(kh)
+M = function(t) {1 + exp(-t/2)}
+vec = M(kh)
+head(vec)
+tail(vec)
+
+covar = function(t_1,t_2) {3/(3+20*(t_2-t_1)^2)}
+cov_mat = matrix(0,nrow = 201,ncol = 201)
+for (i in 1:201)
+  for (j in 1:201)
+    cov_mat[i,j] = covar(kh[i],kh[j])
+cov_mat[1:5,1:5]
+
+eps = rnorm(n+1, mean = 0, sd = 1)
+head(eps)
+tail(eps)
+eps
+
+L = t(chol(cov_mat))
+round(L[1:5,1:5],4)
+res = L %*% t(L)
+res[1:5,1:5]
+
+eta = as.numeric(L %*% eps)
+head(eta)
+tail(eta)
+
+
+ksi = vec + eta
+head(ksi)
+tail(ksi)
+
+
+trajectories = function(Tt, H)
+{
+  n = Tt/H
+  kh = seq(0,Tt,H)
+  vec = M(kh)
+  cov_mat = matrix(0,nrow = 201,ncol = 201)
+  for (i in 1:201)
+    for (j in 1:201)
+      cov_mat[i,j] = covar(kh[i],kh[j])
+  eps = rnorm(n+1, mean = 0, sd = 1)
+  L = t(chol(cov_mat))
+  eta = as.numeric(L %*% eps)
+  ksi = vec + eta
+  return(ksi)
+}
+traj_list = replicate(N, trajectories(Tt, H), simplify = F)
+head(traj_list)
+
+round(traj_list[[1]], 3)
+round(traj_list[[75]], 3)
+round(traj_list[[97]], 3)
+
+trajs = data.frame(x = kh, m_val = vec,
+                   traj_1 = round(traj_list[[1]],3),
+                   traj_75 = round(traj_list[[75]],3),
+                   traj_97 = round(traj_list[[97]],3))
+
+trajs_pl = ggplot(data = trajs, aes(x=x)) + 
+  geom_line(aes(y=m_val,colour="m(t)"), lty = 2, lwd = 2.0) +
+  geom_line(aes(y=traj_1,colour="Trajectory 1"), lwd = 1.6) + 
+  geom_line(aes(y=traj_75,colour="Trajectory 75"), lwd = 1.5) + 
+  geom_line(aes(y=traj_97,colour="Trajectory 97"), lwd = 1.2) +
+  scale_color_discrete(name = "", 
+                       labels = c("m(t)", 
+                                  "Trajectory 1",
+                                  "Trajectory 75",
+                                  "Trajectory 97")) +
+  scale_color_manual(values = c("yellow", "green","red","black")) +
+  labs(title = "Совмещенный график трех траекторий и математического ожидания",x = "", y = "") +
+  theme_classic()
+
+trajs_pl
+
+
+t1 = 1
+t2 = 2
+cut1 = as.data.frame(matrix(c(sapply(traj_list, `[[`, t1),
+                              sapply(traj_list, `[[`, t2)),
+                            ncol = 2, byrow = F))
+colnames(cut1) = c("t1","t2")
+head(cut1)
+
+ggplot(cut1, aes(x = t1, y = t2)) + geom_point() +
+  labs(title = "Диаграмма рассеяния",
+       subtitle = "t1 = 1, t2 = 2",
+       x = "t1", y = "t2") +
+  theme_bw()
+
+
+r = (sum((cut1$t1 - mean(cut1$t1))*
+           (cut1$t2 - mean(cut1$t2))))/ 
+  (sqrt(sum((cut1$t1 - mean(cut1$t1))^2) *
+          sum((cut1$t2 - mean(cut1$t2))^2)))
+r
+
+tanh(atanh(r)-r/(2*(100-1))-qnorm(0.975)/sqrt(100-3))
+tanh(atanh(r)-r/(2*(201-1))+qnorm(0.975)/sqrt(201-3))
+
+cor.test(cut1$t1,cut1$t2,method = "pearson")
+
+r_tr = cov_mat[t1,t2]/sqrt(cov_mat[t1,t1] * cov_mat[t2,t2])
+r_tr
+
+
+t1 = 10
+t2 = 15
+cut1 = as.data.frame(matrix(c(sapply(traj_list, `[[`, t1),
+                              sapply(traj_list, `[[`, t2)),
+                            ncol = 2, byrow = F))
+colnames(cut1) = c("t1","t2")
+head(cut1)
+
+ggplot(cut1, aes(x = t1, y = t2)) + geom_point() +
+  labs(title = "Диаграмма рассеяния",
+       subtitle = "t1 = 10, t2 = 15",
+       x = "t1", y = "t2") +
+  theme_bw()
+
+
+r = (sum((cut1$t1 - mean(cut1$t1))*
+           (cut1$t2 - mean(cut1$t2))))/ 
+  (sqrt(sum((cut1$t1 - mean(cut1$t1))^2) *
+          sum((cut1$t2 - mean(cut1$t2))^2)))
+r
+
+cor.test(cut1$t1,cut1$t2,method = "pearson")
+
+r_tr = cov_mat[t1,t2]/sqrt(cov_mat[t1,t1] * cov_mat[t2,t2])
+r_tr
+
+
+t1 = 30
+t2 = 90
+cut1 = as.data.frame(matrix(c(sapply(traj_list, `[[`, t1),
+                              sapply(traj_list, `[[`, t2)),
+                            ncol = 2, byrow = F))
+colnames(cut1) = c("t1","t2")
+head(cut1)
+
+ggplot(cut1, aes(x = t1, y = t2)) + geom_point() +
+  labs(title = "Диаграмма рассеяния",
+       subtitle = "t1 = 30, t2 = 90",
+       x = "t1", y = "t2") +
+  theme_bw()
+
+
+r = (sum((cut1$t1 - mean(cut1$t1))*
+           (cut1$t2 - mean(cut1$t2))))/ 
+  (sqrt(sum((cut1$t1 - mean(cut1$t1))^2) *
+          sum((cut1$t2 - mean(cut1$t2))^2)))
+r
+
+cor.test(cut1$t1,cut1$t2,method = "pearson")
+
+r_tr = cov_mat[t1,t2]/sqrt(cov_mat[t1,t1] * cov_mat[t2,t2])
+r_tr
+
+paste0(format(round(as.numeric(unlist(cut1['t2'])),3),nsmall = 3), collapse=",")
+covar(t1,t1)
+vec[t2+1]
+vec
-- 
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