velocity.py reads in GROMACS trr trajectory (that inclides velocity information) and calculates center of mass translational velocity and angular velocity. It also computes translational and ...

Learn how to use Python and statistical tools to check for stationarity and autocorrelation in your time series data, and why they matter for analysis and forecasting.

If you are using Python for machine learning, you can use various libraries and functions to test for autocorrelation. For example, you can use the pandas library to create plots and graphs with ...

The partial autocorrelation function (PACF), on the other hand, is more beneficial during the definition phase for an autoregressive model. Partial autocorrelation plots can be used to specify ...

We utilize Python to run ADF test on the return series. The test statistic is -19.5 and the p-value is zero. ... We then proceed to examine the autocorrelation functions of VXX returns.

Simulation of stationary random processes (time series) is an essential engineering tool for system prototyping, design, and optimization. To create a simulation, a randomly generated time series must ...

A new family of ternary sequences with ideal two-level autocorrelation function Abstract: Let /spl alpha/ be a primitive element of F/sub 3n/. Let d=3/sup 2k/-3/sup k/+1 where n=3k.

This repository contains Python functions for predicting time series. ... It also computes translational and rotational kinetic energies, temperatures, velocity autocorrelation functions and power ...