|Statement||Nick T. Thomopoulos.|
|LC Classifications||HD30.27 .T56|
|The Physical Object|
|Pagination||xiv, 369 p. :|
|Number of Pages||369|
|LC Control Number||79000266|
This book provides a lot of good advice about how to actually apply the mathematical techniques introduced to the real world. The chapters on long term forecasting are often startlingly insightful when read today, nearly 16 years after the book was by: Additional Physical Format: Online version: Thomopoulos, Nicholas T. Applied forecasting methods. Englewood Cliffs, N.J.: Prentice-Hall, © (OCoLC) This book describes the methods used to forecast the demands at inventory holding locations. The methods are proven, practical and doable for most applications, and pertain to demand patterns that are horizontal, trending, seasonal, promotion and multi-sku. Forecasting: methods and applications. This book was published in , and for nearly 20 years I maintained an associated website at this address. The data sets from the book can be found in the fma package for R. The solutions to exercises can be downloaded here. The book is now out-of-date.
This is an excellent book on applied time series methods at a basic level. All methods used are in time domain. They include straightforward regression, exponential smoothing, ARIMA models and dynamic regression models popular in economics. The focus is on finding a suitable description of a time series and interpreting s: ~ Best Book New Product Forecasting An Applied Approach ~ Uploaded By Penny Jordan, analogous to new product forecasting is the challenge of forecasting immediately after a catastrophic event like the terrorist attacks of september 11 or the rapid collapse of financial institutions around ten years ago when structural. 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. This is first and foremost a book aimed at applying time series methods to solve real-world forecasting problems. Applied Economic Forecasting using Time Series Methods starts with a brief review of basic regression analysis with a focus on specific regression topics relevant for forecasting, such as model specification errors, dynamic models and their predictive properties as well as forecast .
Applied Economic Forecasting using Time Series Methods starts with a brief review of basic regression analysis with a focus on specific regression topics relevant for forecasting. The author makes a clear declaration about the best method and demonstrates its use throughout the book. The second skill is testing, and the author demonstrates how to divide historical sales data into in- and out-samples, calibrate models on the in-sample, and assess model accuracy by forecasting /5(7). Known from its last editions as the Bible of Forecasting, the third edition of this authoritative text has adopted a new approach-one that is as new as the latest trends in the field: Explaining the past is not adequate for predicting the future. In other words, accurate forecasting requires more than just the fitting of models to historical data. Inside, readers will find the latest. Quantitative forecasting can be applied when two conditions are satisfied: numerical information about the past is available; it is reasonable to assume that some aspects of the past patterns will continue into the future. There is a wide range of quantitative forecasting methods, often developed within specific disciplines for specific purposes.