The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Javier Miranda - One of the best experts on this subject based on the ideXlab platform.
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expanding the role of synthetic data at the u s Census Bureau
2014Co-Authors: Ron S Jarmin, Thomas A Louis, Javier MirandaAbstract:National Statistical offices (NSOs) create official statistics from data collected from survey respondents, government administrative records and other sources. The raw source data is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of users to extract as much information from the data as possible. Traditional disclosure protection techniques result in official data products that do not fully utilize the information content of the underlying microdata. Typically, these products take the form of simple aggregate tabulations. In a few cases anonymized public- use micro samples are made available, but these face a growing risk of re-identification by the increasing amounts of information about individuals and firms available in the public domain. One approach for overcoming these risks is to release products based on synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata. We discuss re- cent Census Bureau work to develop and deploy such products. We discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.
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expanding the role of synthetic data at the u s Census Bureau
Statistical journal of the IAOS, 2014Co-Authors: Ron S Jarmin, Thomas A Louis, Javier MirandaAbstract:National Statistical offices (NSOs) create official statistics from data collected directly from survey respondents, from government administrative records and from other third party sources. The raw source data, regardless of origin, is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of data users to extract as much information as possible from rich microdata. Traditional disclosure protection techniques applied to resolve this tension have resulted in official data products that come no where close to fully utilizing the information content of the underlying microdata. Typically, these products take for the form of basic, aggregate tabulations. In a few cases anonymized public-use micro samples are made available, but these are increasingly under risk of reidentification by the ever larger amounts of information about individuals and firms that is available in the public domain. One potential approach for overcoming these risks is to release products based on synthetic or partially synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata rather than making the actual underlying microdata available. We discuss recent Census Bureau work to develop and deploy such products. We also discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.
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201 -Accessing Business Data Available in the U.S. Census Bureau's Research Data Center Network
2011Co-Authors: Javier Miranda, Shawn D. Klimek, Erika Mcentarfer, Randy A. Becker, Cheryl Grim, James C. DavisAbstract:Javier Miranda, Census Research Data Center Network , U.S. Census Bureau. Shawn D. Klimek, U.S. Census Bureau. Erika McEntarfer, LEHD Economic Research Group, Center for Economic Studies, U.S. Census Bureau. Randy A. Becker and Cheryl A. Grim, Center for Economic Studies, U.S. Census Bureau. James C. Davis, Boston Census Research Data Center, Center for Economic Studies, U.S. Census Bureau.
Regional Offices - One of the best experts on this subject based on the ideXlab platform.
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Chicago Region - U.S. Census Bureau
2009Co-Authors: Regional OfficesAbstract:United States Census Bureau, Chicago Regional Office responsible for servicing the states of Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, Arkansas under New Regional Office Structure effective 1 January 2013
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Philadelphia Region - U.S. Census Bureau
2009Co-Authors: Regional OfficesAbstract:United States Census Bureau, Philadelphia Regional Office responsible for servicing the states of Pennsylvania, District of Columbia, Maryland, Virginia, Delaware, Ohio, Kentucky, Tennessee, West Virginia under New Regional Office Structure effective 1 January 2013
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Denver Region - U.S. Census Bureau
2009Co-Authors: Regional OfficesAbstract:United States Census Bureau, Denver Regional Office responsible for servicing the states of Colorado, Arizona, Utah, Wyoming, Montana, North Dakota, South Dakota, Nebraska, Kansas, Oklahoma, and Texas under New Regional Office Structure effective 1 January 2013
Ron S Jarmin - One of the best experts on this subject based on the ideXlab platform.
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expanding the role of synthetic data at the u s Census Bureau
2014Co-Authors: Ron S Jarmin, Thomas A Louis, Javier MirandaAbstract:National Statistical offices (NSOs) create official statistics from data collected from survey respondents, government administrative records and other sources. The raw source data is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of users to extract as much information from the data as possible. Traditional disclosure protection techniques result in official data products that do not fully utilize the information content of the underlying microdata. Typically, these products take the form of simple aggregate tabulations. In a few cases anonymized public- use micro samples are made available, but these face a growing risk of re-identification by the increasing amounts of information about individuals and firms available in the public domain. One approach for overcoming these risks is to release products based on synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata. We discuss re- cent Census Bureau work to develop and deploy such products. We discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.
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expanding the role of synthetic data at the u s Census Bureau
Statistical journal of the IAOS, 2014Co-Authors: Ron S Jarmin, Thomas A Louis, Javier MirandaAbstract:National Statistical offices (NSOs) create official statistics from data collected directly from survey respondents, from government administrative records and from other third party sources. The raw source data, regardless of origin, is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of data users to extract as much information as possible from rich microdata. Traditional disclosure protection techniques applied to resolve this tension have resulted in official data products that come no where close to fully utilizing the information content of the underlying microdata. Typically, these products take for the form of basic, aggregate tabulations. In a few cases anonymized public-use micro samples are made available, but these are increasingly under risk of reidentification by the ever larger amounts of information about individuals and firms that is available in the public domain. One potential approach for overcoming these risks is to release products based on synthetic or partially synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata rather than making the actual underlying microdata available. We discuss recent Census Bureau work to develop and deploy such products. We also discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.
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resolving the tension between access and confidentiality past experience and future plans at the u s Census Bureau
2009Co-Authors: Lucia Foster, Ron S Jarmin, Lynn T RiggsAbstract:This paper provides an historical context for access to U.S. Federal statistical data with a primary focus on the U.S. Census Bureau. We review the various modes used by the Census Bureau to make data available to users, and highlight the costs and benefits associated with each. We highlight some of the specific improvements underway or under consideration at the Census Bureau to better serve its data users, as well as discuss the broad strategies employed by statistical agencies to respond to the challenges of data access.
Esmd - One of the best experts on this subject based on the ideXlab platform.
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North American Industry Classification System (NAICS), Concordances - US Census Bureau
2019Co-Authors: EsmdAbstract:Concordances-a description of the direct relationshp between classification systems - North American Industry Classification System (NAICS) - US Census Bureau
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Win Genhol Documentation - X-13ARIMA-SEATS Seasonal Adjustment Program - US Census Bureau
2015Co-Authors: Related Methods Staff, EsmdAbstract:US Census Bureau - describes how to run Win Genhol, the Windows interface program for Genhol, a utility that generates user-defined moving holiday regressors for X-13ARIMA-SEATS
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US Census Bureau - X-13ARIMA-SEATS - Win X-13
2013Co-Authors: Related Methods Staff, EsmdAbstract:US Census Bureau - home page for Win X-13 program, a Windows interface to the X-13ARIMA-SEATS Seasonal Adjustment program. This interface will create the input files necessary for seasonally adjusting a series with X-13ARIMA-SEATS, run X-13ARIMA-SEATS and display the output files, create a data table with model information and diagnostics from series run in X-13ARIMA-SEATS, create graphs from X-13ARIMA-SEATS output.
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US Census Bureau - X-13ARIMA-SEATS Seasonal Adjustment Program - X-13-Graph Java
2012Co-Authors: Related Methods Staff, EsmdAbstract:US Census Bureau - Information related to the X-13-Graph Java program, including links for downloading and installation instructions.
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US Census Bureau - X-13ARIMA-SEATS Seasonal Adjustment Program - Dowloading X-13-Graph Batch
2012Co-Authors: Related Methods Staff, EsmdAbstract:US Census Bureau - Links to download the X-13-Graph Batch utility, as well as the interface to the batch program.
Frank Nuessel - One of the best experts on this subject based on the ideXlab platform.
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Addendum to A Note on the 25 Most Frequent Surnames from the 2000 United States Census Bureau List
Names, 2017Co-Authors: Frank NuesselAbstract:This addendum to Nuessel discusses very recently released results on surname frequency in the US provided by the US Census Bureau. That Bureau said that it would no longer prepare an updated list of the 1,000 most frequent surnames in the US because of limited resources. In late 2016, the US Census Bureau released these data from the 2010 Census. This note provides information based on that unanticipated release.
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A Note on the 25 Most Frequent Surnames from the 2000 United States Census Bureau List
Names, 2017Co-Authors: Frank NuesselAbstract:This note uses the United States Census Bureau database of the 1,000 most frequent surnames from the US Census of 2000. It discusses briefly the meaning and origin of the notion of surname. It provides a table of the 25 most frequent surnames in the US from the 2000 Census data, including number of people with the surname, and its meaning. This article provides the reader with three useful onomastic research tools for surnames: (1) The US Census Bureau’s list of the 1,000 most frequently occurring surnames for 2000; (2) Patrick Hanks’ Dictionary of American Surnames; and (3) the National Geographic interactive surname list.