R:搜索具有系数(phi_1和phi_2)的模拟AR(2)的右种子

Question

我希望R搜索将simulate`AR(2(:的seed(s)

ar1.2 <- arima.sim(n = 100, model=list(ar=c(0.5, 0.4), order = c(2, 0, 0)), sd = 1)

这样当我运行以下程序时：

set.seed()
ar1.2 <- arima.sim(n = 100, model=list(ar=c(0.5, 0.4), order = c(2, 0, 0)), sd = 1)
auto.arima(ar1.2)

它将确认AR- coefficients为phi_1 = 0.5...和phi_2 = 0.4...

按时间顺序，我有两个条件需要满足，如下所示：

1. 确保ARIMA order是(2, 0, 0)
2. 在满足上述condition 1的seeds中，其系数为0.5...和0.4...的search

编辑

对`AR(1(进行如下操作：

FUN <- function(i) {
set.seed(i)
ar1 <- arima.sim(n=100, model=list(ar=0.4, order=c(1, 0, 0)), sd=1)
ar2 <- auto.arima(ar1, ic="aicc")
c(arimaorder(ar2), seed=i)
}
R <- 24000  ## this would be your 1e5
seedv <- 23000:R
library(parallel)
cl <- makeCluster(detectCores() - 1 + 1)
clusterExport(cl, c("FUN"), envir=environment())
clusterEvalQ(cl, suppressPackageStartupMessages(library(forecast)))
res <- parSapply(cl, seedv, "FUN")
stopCluster(cl)
seed_out <- res["seed", which(apply(res, 2, function(x) all(x[1:3] == c(1, 0, 0))))]

#########################################################################
sink("ARIMA.SIM_n20_ar0.4.txt")
##########################################################################
arima_order_results = data.frame()
for (my_seed in seed_out){
set.seed(my_seed)
ar1 <- arima.sim(n = 100, model=list(ar=0.4, order = c(1, 0, 0)), sd = 1)
ar2 <- auto.arima(ar1, ic = "aicc")
arr <- as.data.frame(t(ar2$coef))
if(substr(as.character(arr[1]), 1, 5) == "0.400") {
arr <- cbind(data.frame(seed=my_seed),arr)
print(arr)
arima_order_results = bind_rows(arima_order_results,arr)
# write.csv(my_seed, paste0(arr, ".csv"), row.names = FALSE)
}
}
##########################################################################
sink()
#######################################################################

在工作目录中获取输出

#seed       ar1
#1 23027 0.4009039
#seed       ar1 intercept
#1 23305 0.4005298 0.4055362
#seed       ar1
#1 23443 0.4004223
#seed      ar1
#1 23845 0.400621

我用seed of 23027确认输出

set.seed(23027)
ar1 <- arima.sim(n=100, model=list(ar=0.4, order=c(1, 0, 0)), sd=1)
library(forecast)
auto.arima(ar1, ic="aicc")

AR(1(情况下的parallel and better Answer在这里是

我想要这样一个AR(2(的解决方案

Answer 1

我使用了上面问题中链接的解决方案中的方法。我也使用ar1 = 0.3，而ar2 = 0.4

FUN2 <- function(i) { 
set.seed(i) 
ar1 <- arima.sim(n=20, model=list(ar=c(0.3, 0.4), order=c(2, 0, 0)), sd=1) 
ar2 <- auto.arima(ar1, ic="aicc") 
(cf <- ar2$coef) 
if (length(cf) == 0) { 
rep(NA, 2) 
} 
else if (all(grepl(c("ar1|ar2|intercept"), names(cf))) & 
substr(cf["ar1"], 1, 3) %in% "0.3" & substr(cf["ar2"], 1, 3) %in% "0.4") { 
c(cf, seed=i) 
} 
else { 
rep(NA, 2) 
} 
}
R <- 1e4 
seedv <- 1:R 
library(parallel) 
cl <- makeCluster(detectCores() - 1 + 1) 
clusterExport(cl, c("FUN2"), envir=environment()) 
clusterEvalQ(cl, suppressPackageStartupMessages(library(forecast))) 
res <- parLapply(cl, seedv, "FUN2") 
(res1 <- res[!sapply(res, anyNA)]) 
stopCluster(cl) 
res2 <- Reduce(function(...) merge(..., all=T), lapply(res1, function(x) 
as.data.frame(t(x)))) 
res2[order(res2$seed), ]