Simulation of a stochastic processes with drift

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How to simulate a stochastic process with drift? Can anyone explain?
Aug 30, 2019 in Data Analytics by anonymous
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1 answer to this question.

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Check out below code. It's an example to simulate random walk with drift.

library(dplyr)
library(ggplot2)
rerun(5, rnorm(100)) %>%
  set_names(paste0("sim", 1:5)) %>%
  map(~ accumulate(., ~ .05 + .x + .y)) %>%
  map_dfr(~ tibble(value = .x, step = 1:100), .id = "simulation") %>%
  ggplot(aes(x = step, y = value)) +
  geom_line(aes(color = simulation)) +
  ggtitle("Simulations of a random walk with drift")

In the above code, rerun creates sample data 5 times .map_dfr() return data frames created by row-binding and column-binding respectively. accumulate returns data point values from random values.

answered Aug 30, 2019 by anonymous
• 32,460 points

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