Time Series Forecasting Using Machine Learning : Case Studies with R and Iforecast - Tsung-wu Ho

Instant online reading.
Don't wait for delivery!

Time Series Forecasting Using Machine Learning

Case Studies with R and Iforecast

By: Tsung-wu Ho

Write A Review

Hardcover | 4 October 2025

At a Glance

Hardcover
144 Pages

Dimensions(cm)
23.5 x 15.5 x 0.97

Hardcover

$229.00

or 4 interest-free payments of $57.25 with

Ships in 5 to 7 business days

This book uses R package, iForecast, to conduct financial economic time series forecasting with machine learning methods, especially the generation of dynamic forecasts out-of-sample. Machine learning methods cover enet, random forecast, gbm, and autoML etc., including binary economic time series. The book explains the problem about the generation of recursive forecasts in machine learning framework, under which, there are no covariates, namely, input (independent) variables. This case is pretty common in real decision environment, for example, the decision-making wants 6-month forecasts in the real future, under which there are no covariates available; therefore, practitioners use recursive or multistep, forecasts. Besides macro-econometric modelling which uses VAR (vector autoregression) to overcome the problem of multivariate regression, this book offers a Machine-Learning VAR routine, which is found to improve the performance of multistep forecasting.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $0.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.