Beer national sales forecasting
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Updated
Aug 28, 2018 - Python
Beer national sales forecasting
Sentiment analysis of Reddit comments to predict bitcoin price movement
This code is a demonstration of how to implement a VAR model. I estimate the VAR coefficients and then compare those with the results from a statsmodels package. The results are identical. This is a nice way to understand the steps behind estimating a VAR. This would also help to connect the concepts VAR and SUR.
Exploration of environmental variables and death over time
Personal repository for hobby and work projects
Multivariate time series analysis on london bike sharing dataset
Analysis scripts and randomly generated data for Suicide and Life-Threatening Behavior paper: 'Identifying person-specific coping responses to suicidal urges: A case series analysis and illustration of the idiographic method'
Tanulmányomban az egy főre eső GDP és munkanélküliség teljes termékenységi arányszámra gyakorolt hatását elemzem. A választott eszközök között szerepel az Engel-Granger kointegrációs teszt, amellyel megerősítettem a hipotézist, hogy szomszédos országok termékenységi rátájának alakulása általában nagyobb egyezőséget mutat, melynek magyarázata leh…
Utilized sentiment-based features to predict cryptocurrency returns, models used: Random Forest Classifier, Random Forest Regressor, and VAR time-series model
Manipulation of time series data and forecast CAD/USD currency using commodities
Forecasting with VAR
Codebase for Term Paper of course ECON F244: Economics of Growth and Development at BITS Pilani, Pilani campus (Spring '21)
Repository for: Chiovaro, M., Windsor, L. C., & Paxton, A. (2021). Vector Autoregression, Cross-Correlation, and Cross-Recurrence Quantification Analysis: A Case Study in Social Cohesion and Collective Action. In CogSci.
Interactive Notebook demonstrating the R-library bigtime
Unemployment Rate forecasting tool built for BMWi during the Data Science for Social Good Fellowship https://dssgxuk.github.io/bmwi/
Forecasting exchange rates by using commodities prices
Remaining useful life estimation of NASA turbofan jet engines using data driven approaches which include regression models, LSTM neural networks and hybrid model which is combination of VAR with LSTM
Time Series Forecasting for the M5 Competition
The purpose of my application was to solve a problem many businesses (small businesses in particular) face. They do not know how much to produce, where to price, how much to spend on advertising and many other questions. Eden’s purpose was to answer these questions for them easily and with no technical acumen required by the user. Eden would mod…
Respiratory Health Recommendation System based on Air Quality Index Forecasts
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