I use the accuracy function in the forecast package to get model accuracy metrics of a time series I obtained through the following steps: Simulate a 10 sample of AR(1) series. Split the series into subseries of size 2 without overlapping. Resample the subseries 1000 times with replacement. Form a new series by joining all ..
I wish to run for loop in parallel process. The result I have with the for loop R code is good to my taste but will be applying it to a very huge data thus, the timing of the execution is slow. library(forecast) library(dplyr) arima_order_results = data.frame() seed_out2 <- c(1, 16, 170, 178, 411, 630, ..
I Have an R code that helps me to know at what seed when I use arima.sim() function to simulate ARIMA(1, 0, 0) it will actually simulate ARIMA of order 1, 0, 0 when auto.arima() function is employed for a check. MWE library(forecast) SEED_vector <- 1:10 arima_order_results <- data.frame() flag <- TRUE i <- 1 ..
I have R scrip that simulates ARIMA data and check the same data 100 times for ARIMA order ARIMA(p, d, q). I have 2 core on the system CPU, how can I give an R command for a core to compute 1 to 50 while the second core to compute 51 to 100 simultaneously and ..