Multivariate time series Vector Autoregression Model (VAR) on real world GDP and DPI (and some other indexes). Bayesian Structured Time Series (BSTS).
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Updated
Aug 16, 2022 - Jupyter Notebook
Multivariate time series Vector Autoregression Model (VAR) on real world GDP and DPI (and some other indexes). Bayesian Structured Time Series (BSTS).
Crop yield Forecasting on the basis of meteorological predictions using some Time series & ML models
This repo contains files for the blog post about conjoint analysis
A comprehensive implementation of various Regression Techniques in Machine Learning.
Forecast the Airlines Passengers and CocaCola Prices data set. Prepare a document for model explaining. How many dummy variables you have created and RMSE value for model. Finally which model you will use for Forecasting.
Using Python to work up a Design of Experiments
My this project repository focused on hypothesis testing involving T-test, Chi-square test, Binomial Test, ANOVA, Sample Size Determination with scipy, statmodels modules.
Tutorials for BSE classes.
Influence of 17-AAG a Hsp90 inhibitor on signaling pathway in Atopic Dermatitis
Project analyzes the price trends, correlations, and patterns of Bitcoin, Ethereum, and Binance Coin (2020–2024) using Python and statistical methods. It explores volatility, trends, seasonality, and forecasts future prices while assessing interdependencies and stability during major economic events.
Apprentissage supervisé : Création de modèles prédictifs
Predict delivery time using sorting time and Build a prediction model for salary hike.
Created model using Linear regression to predict variables impacting demand.
Анализ соответствия размера выборки и плановых значений метрик A/B-теста
Used libraries and functions as follows:
ExcelR Data Science Assignment No 3
Exploration of descriptive and inferential statistical methods using Python and Jupyter Notebook.
Autoregressive (AR) models with advanced techniques: model selection, diagnostics, structural breaks, rolling forecasts, Fourier seasonality, exogenous variables, business cycle analysis, and benchmarking for economic time series.
Tried to understand whether the company should implement a new page or keep the old page with some statistical techniques.
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