Implementing Time Series Auto Regressive Model (AR Model) from Scratch in Python

使用经典的AR、MA、ARMA、ARIMA、ARCH、GARCH时间序列模型进行模型的检验和拟合。The classic AR, MA, ARMA, ARIMA, ARCH, GARCH time series models are used to test and predict the model.

Combined study of two biological signals: EEG Power Variability and Middle Cerebral Artery Blood Flow Velocity

iOS face-beautification toolkit built upon FaceUnity Nama SDK and FULiveDemo. 相芯美颜 SDK 集成工具包。

In the second semester of 2021 - 2022, I took the course "Stochastic Process", which included programming exercises and projects in MATLAB language in the above files and you can see.

In this section, we will estimate airline passengers using time series methods.

In this section, we will examine the Statistical Methods in time series analysis.

Assignment codes for EE779 Advanced Topics in Signal Processing

AutoRegressive(AR), Moving Average(MA), AutoRegressive Integrated Moving Average(ARIMA) Model

This repository focuses on predicting Apple Inc.'s stock prices using time series analysis from 2013 to 2018. The project involves data exploration, stationarity analysis, time series decomposition, model development, and generating insights to assist investors.

PID Tunining with deep neural network from scratch

Analysis of emotion dynamics in dyadic conversations from 3 (self, partner, 5 external observers) annotation perspectives

To predict the future price for a time series regression problem of bitcoin. Predicting the future price of Bitcoin can be helpful for investors to make informed decisions about buying and selling Bitcoin

Demonstration of time series analysis using various concepts and models.

Time Series Analysis and Forecasting

Semester Project for Timeseries Course / Aristotle University of Thessaloniki / Winter Semester 2020

Predictive analysis of Hermes and BlackRock financial returns using AR and ARMA models for dynamic portfolio management.

Detailed implementation of various time series analysis models and concepts on real datasets.