simulate timeseries data in matlab

You can simulate time series data in MATLAB using various methods. One of the most common methods is to generate a random process with specific statistical properties.

Here's an example of how to generate a simulated time series data using the autoregressive (AR) model:

main.m
% Parameters for the AR model
order = 2;         % order of the AR model
coefficients = [0.8, -0.4];  % AR coefficients
variance = 1;      % variance of the white noise

% Length of the time series
N = 1000;

% Generate white noise with zero mean and unit variance
white_noise = sqrt(variance) * randn(N, 1);

% Initialize the time series vector
time_series = zeros(N, 1);

% Generate the time series using the AR model
for t = order + 1:N
    time_series(t) = coefficients(1) * time_series(t-1) + coefficients(2) * time_series(t-2) + white_noise(t);
end

% Plot the time series
plot(time_series);
598 chars
22 lines

This code generates a time series data of length N by using an AR model with order 2 and specified coefficients. The white noise component is generated using a random number generator and added to the AR model to create the time series data.

You can modify the parameters (order, coefficients, variance, N) to simulate different time series data as per your requirements.

Hope this helps you to simulate time series data in MATLAB!