random-walk

问题 I'm new to the forum and a beginner in programming. I have the task to program a random walk in Matlab (1D or 2D) with a variance that I can adjust. I found the code for the random walk, but I'm really confused where to put the variance. I thought that the random walk always has the same variance (= t ) so maybe I'm just lost in the math. How do I control the variance? 回答1: For a simple random walk, consider using the Normal distribution with mean 0 (also called 'drift') and a non-zero

问题 I am attempting to write a program that executes Monte Carlo simulations using OpenCL. I have run into an issue involving exponentials. When the value of the variable steps becomes large, approximately 20000, the calculation of the exponent fails unexpectedly, and the program quits with "Abort Trap: 6". This seems to be a bizarre error given that steps should not affect memory allocation. I have tried setting normal , alpha , and beta to 0 but this does not resolve the problem however

问题 I'm simulating a one-dimensional and symmetric random walk procedure: y[t] = y[t-1] + epsilon[t] where white noise is denoted by epsilon[t] ~ N(0,1) in time period t . There is no drift in this procedure. Also, RW is symmetric, because Pr(y[i] = +1) = Pr(y[i] = -1) = 0.5 . Here's my code in R: set.seed(1) t=1000 epsilon=sample(c(-1,1), t, replace = 1) y<-c() y[1]<-0 for (i in 2:t) { y[i]<-y[i-1]+epsilon[i] } par(mfrow=c(1,2)) plot(1:t, y, type="l", main="Random walk") outcomes <- sapply(1

问题 I have a Matlab code that generates a 1D random walk. %% probability to move up or down prob = [0.05, 0.95]; start = 2; %% start with 2 positions(1) = start; for i=2:1000 rr = rand(1); down = rr<prob(1) & positions(i-1)>1; up = rr>prob(2) & positions(i-1)<4; positions(i) = positions(i-1)-down + up; figure(1), clf plot(positions) This gives me the plot below 1D Random Walk with Matlab I need to try to translate this in Python and I have came up with this (using numpy): import random import

问题 I have a Matlab code that generates a 1D random walk. %% probability to move up or down prob = [0.05, 0.95]; start = 2; %% start with 2 positions(1) = start; for i=2:1000 rr = rand(1); down = rr<prob(1) & positions(i-1)>1; up = rr>prob(2) & positions(i-1)<4; positions(i) = positions(i-1)-down + up; figure(1), clf plot(positions) This gives me the plot below 1D Random Walk with Matlab I need to try to translate this in Python and I have came up with this (using numpy): import random import

问题 I'm simulating a 2-dimensional random walk, with direction 0 < θ < 2π and T=1000 steps. I already have a code which simulates a single walk, repeats it 12 times, and saves each run into sequentially named text files: a=np.zeros((1000,2), dtype=np.float) print a # Prints array with zeros as entries # Single random walk def randwalk(x,y): # Defines the randwalk function theta=2*math.pi*rd.rand() x+=math.cos(theta); y+=math.sin(theta); return (x,y) # Function returns new (x,y) coordinates x, y =

问题 I am trying to generate a random tour from the graph. I am using the adjacency-list method. There is a problem with the vertices. When I add a vertex to a particular list, the vertex gets added to all the lists in the graph. I do not understand why! Here's the code: public static void main(String[] args) { defaultData(6); } public static void defaultData(int n) { Integer costs[] = { 26, 95, 38, 74, 80, 73, 73, 92, 22, 97, 13, 81, 41, 17, 4, 2, 47, 54, 21, 68, 78, 4, 77, 3, 66, 55, 99, 42, 62,

问题 I'm building a biased correlated random walk, and I've managed to build the RW, and bias it for westerly movement. The issue: I need the walk to be bound on one (or all) side(s). The current code is: walk<-function(n.times){ plot(524058:542800,2799758:2818500,type="n", xlab="Easting",ylab="Northing")#aren‌​a y<-2815550 ##startY x<-542800 #startX N<-4000 E<-4000 points(x,y,pch=16,col="red",cex=1) for (i in 1:n.times) { yi <- sample(c(N,N/2,N/4,N/8,N/12,N/16, 0,-N,-N/2,-N/4,-N/8,-N/12,-N/16),1)

问题 I'm building a biased correlated random walk, and I've managed to build the RW, and bias it for westerly movement. The issue: I need the walk to be bound on one (or all) side(s). The current code is: walk<-function(n.times){ plot(524058:542800,2799758:2818500,type="n", xlab="Easting",ylab="Northing")#aren‌​a y<-2815550 ##startY x<-542800 #startX N<-4000 E<-4000 points(x,y,pch=16,col="red",cex=1) for (i in 1:n.times) { yi <- sample(c(N,N/2,N/4,N/8,N/12,N/16, 0,-N,-N/2,-N/4,-N/8,-N/12,-N/16),1)

问题 I am trying to quickly create a simulated random walk series in pandas. import pandas as pd import numpy as np dates = pd.date_range('2012-01-01', '2013-02-22') y2 = np.random.randn(len(dates))/365 Y2 = pd.Series(y2, index=dates) start_price = 100 would like to build another date series starting at start_price at beginning date and growing by the random growth rates. pseudo code: P0 = 100 P1 = 100 * exp(Y2) P2 = P1 * exp(Y2) very easy to do in excel, but I cant think of way of doing it