This is a note on how to use my package bayesQVAR and the technical details on QVAR estimation, forecasting and quantile impulse response … Read more →

Economics 395: Forecasting […] This resource is a compilation of Dr. Jaya Jha’s notes and code for Economics 395: Economic Forecasting. This course uses Introduction to Time Series Analysis and Forecasting as the primary textbook.1 The code sections for this class use the same data and visualizations from Introduction to Time Series Analysis and Forecasting, but not the methods.2 The methods used are from Forecasting: Principles and Practice by Rob J. Hyndman and George Athanasopoulos.3 Montgomery, Jennings, and Kulahci, Introduction to Time Series Analysis and Forecasting.↩︎ Montgomery, … Read more →

Time series analysis using R. […] These notes are based on the Time Series with R skill track at DataCamp and Rob Hyndman’s Forecasting: Principles and Practice (Rob J Hyndman 2021). I organized them into a section on working with a tsibble (time series tibble) (chapter 1), a section on data exploration (chapter 2), and then four sections on models. Forecasts aren’t necessarily based on time series models - you can perform a cross-sectional regression analysis of features, possibly including time-related features such as month of year (chapter 3). Time series forecasts are a specific type … Read more →

Business Statistics […] The course purpose is to introduce a formal framework for analyzing real life business problems with actual data, so that students can improve their understanding of the circumstances in which statistical techniques should be used and how to apply statistics to practical business situations. The entire course is supported with many case studies and worked-out examples. In particular, statistical techniques are grouped in sections covering applications in the field of decision making, business forecasting, quality control, and commonly used descriptive and inferential … Read more →

Class notes for University of Virginia SYS 5581, Spring 2021 […] This document is a compilation of class notes for SYS 5581 Time Series and Forecasting, University of Virginia, Spring, … Read more →

Scripts from the online course on Time Series and Forecasting in R. […] Selecting the model. Due to seasonality involved, simple models will not be able to capture it. We therefore use the seasonal ARIMA and exponential smoothing models. Exponential smoothing models have seasonality built in it by construction. Complex models like mixed models and neural nets will be an overkill. … Read more →

Gijón Air Pollution - An exercise of visualization and forecasting […] My name is Sergio Berdiales and I am a Data Analyst with more than ten years experience in Customer Experience and Quality areas. If you want to know more about me or contact me you can visit my Linkedin profile or my Twitter account. This is my final project for the Kschool Master on Data Science (8th edition). The main objective of this project is to show I can apply the acquired knowledge during the master’s course in a practical way . The Master on Data Science of Kschool is a 230-hour course which includes Python … Read more →

This is a book that contains experiments and results about the predictions of dengue outtbreaks in Thailand. […] This is a sample book written in Markdown. For now, you have to install the development versions of bookdown from Github: … Read more →

This is the second edition of Forecasting: Principles & Practice, which uses the forecast package in R. The third edition, which uses the fable package, is also available. Welcome to our online textbook on forecasting. This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details. The book is … Read more →