Econometric foundations

By R. Mittelhammer, G. Judge, Douglas J. Miller. 2000

452 citations recorded by the source corpus.

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Citations in the corpus

Positive mathematical programming with multiple data points : a cross- sectional estimation procedure (2000, background): “(8) See Golan, Judge and Miller (1996) for a comprehensive introduction to Maximum Entropy Econometrics, or Mittelhammer, Judge, and Miller (2000), chapter E3, in the context of a general Econometrics textbook.”
Forecasting Using Relative Entropy (2005, background): “Then I(π*, π) must be of the form (see Renyi 1961) Iα(π*;π) 1 α(α 1) N i 1 π*i [(π*iπi) α 1] , in the N-outcome discrete case, a measure popularized by Cressie and Read (1984) (see also Mittelhammer, Judge, and Miller, 2000, section 13.4).”
Verifying the Solution from a Nonlinear Solver: A Case Study (2004, background): “Ron C. Mittelhammer et al. (2000) alerts the reader to serious numerical problems that can arise in nonlinear estimation (Sec.”
Entry, exit, and the business cycle: Are cooperatives different? (2006, unknown): “This statistic can be found in Mittelhammer et al. (2000).”
Beta Regression in R (2010, methodology): “All of optim() ’s methods are available but the default is "BFGS" , which is typically regarded to be the best-performing method (Mittelhammer, Judge, and Miller 2000, Section 8.13) with the most eﬀective up-dating formula of all quasi-Newton methods (Nocedal and Wright 1999, p. 197).”
Economic Analysis of Spatial-Temporal Patterns in Corn and Soybean Response to Nitrogen and Phosphorus (2006, background): “Furthermore, no assumptions about the error distribution are required except that errors are independent and identically distributed (Mittelhammer et al., 2000).”