Quantile Regression for Spatial Data is popular PDF and ePub book, written by Daniel P. McMillen in 2012-08-01, it is a fantastic choice for those who relish reading online the Business & Economics genre. Let's immerse ourselves in this engaging Business & Economics book by exploring the summary and details provided below. Remember, Quantile Regression for Spatial Data can be Read Online from any device for your convenience.
Quantile Regression for Spatial Data Book PDF Summary
Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable. Despite its advantages, quantile regression is still not commonly used in the analysis of spatial data. The objective of this book is to make quantile regression procedures more accessible for researchers working with spatial data sets. The emphasis is on interpretation of quantile regression results. A series of examples using both simulated and actual data sets shows how readily seemingly complex quantile regression results can be interpreted with sets of well-constructed graphs. Both parametric and nonparametric versions of spatial models are considered in detail.
Detail Book of Quantile Regression for Spatial Data PDF
- Author : Daniel P. McMillen
- Release : 01 August 2012
- Publisher : Springer Science & Business Media
- ISBN : 9783642318153
- Genre : Business & Economics
- Total Page : 69 pages
- Language : English
- PDF File Size : 7,6 Mb
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