There are 2 repositories under autoregression topic.
NeuralProphet: A simple forecasting package
Official repository for the paper "Chunked Autoregressive GAN for Conditional Waveform Synthesis"
The official implementation for ICMI 2020 Best Paper Award "Gesticulator: A framework for semantically-aware speech-driven gesture generation"
I perform time series analysis of data from scratch. I also implement The Autoregressive (AR) Model, The Moving Average (MA) Model, The Autoregressive Moving Average (ARMA) Model, The Autoregressive Integrated Moving Average (ARIMA) Model, The ARCH Model, The GARCH model, Auto ARIMA, forecasting and exploring a business case.
ARIMA model from scratch using numpy and pandas.
Learning Data Science
This is the official implementation of the paper "Generating Emotive Gaits for Virtual Agents Using Affect-Based Autoregression".
Time Series Analysis Concepts Explained with examples
Forecasting sales and economic demand for businesses with a time series approach using NeuralProphet
Delay Embedded Regressive Reduced Order Model
Matlab Machine Learning application for predicting Arsenal F.C. football results during 2013-2014 season using self-programmed multi-class (1-against-rest approach) Naive Bayes and an implementation of AutoRegression.
This is a final project for a Time Series course. My professor told me I could further work on it.
modeling autonomous guided vehicle using MATLAB Simulink. deterministic and stochastic system identification
Autoregression is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step.
Developed predictive models like ARIMA and logistic regression to analyze market trends and forecast movements. Employed statistical techniques like moving averages for trend insights and binary outcome predictions in financial analysis.
documenting my bachelor thesis
Time-series forecasting models
Analyse underlying causalities of functional processes
COVID-19 Spread Prediction in Pakistan
Novelty Detection
R package that simulates and estimates the hystar model
We predict GDP growth in R, comparing autoregressive models.
Autoregression on eye-gaze yields intent prediction.
:medal_sports: 2019 한국통계학회 춘계학술논문대회 프로젝트
Air Quality in Nairobi (Based on PM2.5 index)- A Time Series Analysis Projects - Building ARIMA ML Model. In this project, I work with data from one of Africa’s largest open data platforms openAfrica https://africaopendata.org/ .I’ll look at air quality data from Nairobi, Lagos, and Dar es Salaam; and build a time seriesmodel to predict PM 2.5 readings throughout the day.
Simple Moving Averages (SMA) and Autoregression (AR) Yule Walker Model for time series data representing temperature change and electrical consumption.
Weather Data Analysis using Python, Pandas, SparkSQL, AutoRegression Model
Prediction of future global land temperature based on accuracy of different models and evaluating which model performs better
R Shiny application for measuring the effect of foods on gastrointestinal symptoms. Public on shinyapps.io
Snippets and Utils for Machine and Deep Learning
Implement gradient descent in linear regression problems, construct and evaluate simple linear models, and use feature engineering to create more complex supervised machine learning models.
Prediction of the temperature in Berlin Tempelhof for the next couple of days. The model predicted 19.3° C for the first unknown day with the actual temperature being 19.8 °C.