{"product_id":"statistical-matching-theory-and-practice-hardcover","title":"Statistical Matching: Theory and Practice - Hardcover","description":"\u003cp\u003eby \u003cb\u003eMarcello D'Orazio\u003c\/b\u003e (Author), \u003cb\u003eMarco Di Zio\u003c\/b\u003e (Author), \u003cb\u003eMauro Scanu\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eThere is more statistical data produced in today's modern society than ever before. This data is analysed and cross-referenced for innumerable reasons. However, many data sets have no shared element and are harder to combine and therefore obtain any meaningful inference from. Statistical matching allows just that; it is the art of combining information from different sources (particularly sample surveys) that contain no common unit. In response to modern influxes of data, it is an area of rapidly growing interest and complexity. \u003ci\u003eStatistical Matching: Theory and Practice\u003c\/i\u003e introduces the basics of statistical matching, before going on to offer a detailed, up-to-date overview of the methods used and an examination of their practical applications. \u003c\/p\u003e\u003cul\u003e \u003cli\u003ePresents a unified framework for both theoretical and practical aspects of statistical matching.\u003c\/li\u003e \u003cli\u003eProvides a detailed description covering all the steps needed to perform statistical matching.\u003c\/li\u003e \u003cli\u003eContains a critical overview of the available statistical matching methods.\u003c\/li\u003e \u003cli\u003eDiscusses all the major issues in detail, such as the Conditional Independence Assumption and the assessment of uncertainty.\u003c\/li\u003e \u003cli\u003eIncludes numerous examples and applications, enabling the reader to apply the methods in their own work.\u003c\/li\u003e \u003cli\u003eFeatures an appendix detailing algorithms written in the R language.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eStatistical Matching: Theory and Practice\u003c\/i\u003e presents a comprehensive exploration of an increasingly important area. Ideal for researchers in national statistics institutes and applied statisticians, it will also prove to be an invaluable text for scientists and researchers from all disciplines engaged in the multivariate analysis of data collected from different sources.\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eThere is more statistical data produced in today's modern society than ever before. This data is analysed and cross-referenced for innumerable reasons. However, many data sets have no shared element and are harder to combine and therefore obtain any meaningful inference from. Statistical matching allows just that; it is the art of combining information from different sources (particularly sample surveys) that contain no common unit. In response to modern influxes of data, it is an area of rapidly growing interest and complexity. \u003ci\u003eStatistical Matching: Theory and Practice\u003c\/i\u003e introduces the basics of statistical matching, before going on to offer a detailed, up-to-date overview of the methods used and an examination of their practical applications. \u003c\/p\u003e\u003cul\u003e \u003cli\u003ePresents a unified framework for both theoretical and practical aspects of statistical matching.\u003c\/li\u003e \u003cli\u003eProvides a detailed description covering all the steps needed to perform statistical matching.\u003c\/li\u003e \u003cli\u003eContains a critical overview of the available statistical matching methods.\u003c\/li\u003e \u003cli\u003eDiscusses all the major issues in detail, such as the Conditional Independence Assumption and the assessment of uncertainty.\u003c\/li\u003e \u003cli\u003eIncludes numerous examples and applications, enabling the reader to apply the methods in their own work.\u003c\/li\u003e \u003cli\u003eFeatures an appendix detailing algorithms written in the R language.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eStatistical Matching: Theory and Practice\u003c\/i\u003e presents a comprehensive exploration of an increasingly important area. Ideal for researchers in national statistics institutes and applied statisticians, it will also prove to be an invaluable text for scientists and researchers from all disciplines engaged in the multivariate analysis of data collected from different sources. \u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eMarcello D'Orazio is the author of Statistical Matching: Theory and Practice, published by Wiley.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 272\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.81 x 9.16 x 6.72 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e May 12, 2006\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42736984883263,"sku":"9780470023532","price":248.75,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/4c2baca607f2f01b0da77c11e6d0fab5.webp?v=1765148476","url":"https:\/\/dhlswag.com\/products\/statistical-matching-theory-and-practice-hardcover","provider":"BBB","version":"1.0","type":"link"}