A general understanding of Statistics Basics, Different tests with Different Python Libraries

This project builds a time series model that forecasts a 3-year industrial production of electic and gas utilities in US.

In the following R code I used packages like "MTS", "urca", "fUnitRoots" to conduct ADF test and Phillips Perron Test on 4-mariate financial data.

Used time series model to forecast

Modelo de machine learning con series temporales que predice la cantidad de taxis para la próxima hora.

One of the most important tasks for any retail store company is to analyze the performance of its stores. The main challenge faced by any retail store is predicting in advance the sales and inventory required at each store to avoid overstocking and under-stocking. This helps the business to provide the best customer experience and avoid getting …

Retail sales forecasting (time series) with Autoregression model in Python

Time Series Analysis of Zillow data

Прогнозирование спроса на такси

Demonstrações de séries temporais com Estacionaridade no Python com valores aleatórios e dados reais.

package for modelling Time Series Processes as locally stationary processes

Analysis of Skewness and Kurtosis in Stock Return data and their Transformations

Performed Exploratory Data Analysis and Time-Series Forecasting on historical stock market data.

Automating time series stationarity tests

Data Science: Machine Learning analysis of B2B website Visits and Purchase Patterns

Time series preprocessing. (G)ARCH, VECM, VAR modeling on stock data.

Using Python for comprehensive data analyses and machine learning, alongside Tableau for advanced data visualization, for a German company seeking to expand their customer base.

This project will show the time series analysis of Global Temperature Dataset which is from 1900 - 2013. It has been build in R programming Language..

A Repository contains how to check stationarity using swath plot or variogram plot