NM-method (original) (raw)
The NM-method or Naszodi–Mendonca method is the operation that can be applied in statistics, econometrics, economics, sociology, and demography to construct counterfactual contingency tables. The method finds the matrix which is “closest” to matrix ( called the seed table) in the sense of being the same but with the . While the row totals and column totals of are known, matrix itself may not be known. Since the for matrix is unique, the NM-method is a function: , where is an all one row vector of size , while is an all one column vector of size .
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dbo:abstract | The NM-method or Naszodi–Mendonca method is the operation that can be applied in statistics, econometrics, economics, sociology, and demography to construct counterfactual contingency tables. The method finds the matrix which is “closest” to matrix ( called the seed table) in the sense of being the same but with the . While the row totals and column totals of are known, matrix itself may not be known. Since the for matrix is unique, the NM-method is a function: , where is an all one row vector of size , while is an all one column vector of size . The NM-method was developed by Naszodi and Mendonca (2021) to solve for matrix in problems, where matrix is not a sample from the population characterized by the row totals and column totals of matrix , but represents another population. (en) |
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rdfs:comment | The NM-method or Naszodi–Mendonca method is the operation that can be applied in statistics, econometrics, economics, sociology, and demography to construct counterfactual contingency tables. The method finds the matrix which is “closest” to matrix ( called the seed table) in the sense of being the same but with the . While the row totals and column totals of are known, matrix itself may not be known. Since the for matrix is unique, the NM-method is a function: , where is an all one row vector of size , while is an all one column vector of size . (en) |
rdfs:label | NM-method (en) |
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