Nonlinear Statistical Models

By R. Gallant. 1988

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Citations in the corpus

Trend analysis of climate time series: A review of methods (2019, methodology): “The general concept and mathematical foundations of nonlinear regression are treated in the books by Gallant (1987) and Seber and Wild (1989). Methods to solve optimization problems are treated by Michalewicz and Fogel (2000). Particularly useful for climatological trend estimations are nonlinear ch”
The estimating function bootstrap (2000, background): “This case is considered by Boos (1992), White (1982), Gallant (1987) and others who give approximate pivotals suitable for testing H0.”
Deterministic global optimization for error-in-variables parameter estimation (2002, methodology): “Accounting for error in all the variables has been demonstrated (e.g., Duever et al., 1987; Patino-Leal and Reilly, 1982) to lead to unbiased estimates of the parameter values, and thus to more accurate models.”
Network quantile autoregression (2019, methodology): “Then the NQAR model degenerates to the network autoregression (NAR) model in the mean case, see Zhu et al. (2016). For convenience, define Yt = (Y1t, · · · , YNt) ∈ R , Z = (Z1, · · · , ZN) ∈ RN×q.”
The Large Sample Behaviour of the Generalized Method of Moments Estimator in Misspecified Models (2003, methodology): “It can be shown that this condition is satisfied by the Bartlett, Parzen and quadratic spectral kernels.”
Solutions Manual and Supplementary Materials for Econometric Analysis of Cross Section and Panel Data (2003, background): “See, for example, Hansen (1982) and Gallant (1987). The GMM distance statistic is simply the di¤erence in the criterion function (8.”
Robust discrimination designs (2009, methodology): “…These pj×pj matrices are Aj.θj/=UTj .θj/ Uj.θj/, MSEn.θj/=E[.θ̂n,j−θj/.θ̂n,j−θj/T]: The MSE matrix is evaluated by using the usual first-order approximations that are common to non-linear regression—see Gallant (1987), chapter 3—to obtain MSEn.θj/=E[.θ̂n,j−E[θ̂n,j ]/.θ̂n,j−E[θ̂n,j ]/T]+ .”
Testing Distributional Assumptions: A GMM Approach (2007, methodology): “1) and the generalized method of moments (GMM) of Hansen (1982) for testing distributional assumptions.”
Additivity in tree biomass components of Pyrenean oak (Quercus pyrenaica Willd.) (2003, methodology): “The tree components considered in this work are stem and crown dry weight, with bark, up to a 2.5 cm top diameter.”
On the LASSO and its Dual (2000, background): “(A.3) Thus, we may approximate the variance matrix of β∗c,I by (see, among others, Gallant, 1987, Chapter 3.7) (A + Wc,I) −1 A (A + Wc,I) −1 σ̂2.”
Liquidity, Default, Taxes and Yields on Municipal Bonds (2008, unknown): “K ) degrees of freedom if the disturbance term is normal under the null hypothesis that the restricted coefficients are zero ( see Gallant , 1987 ) .”
Market States and Momentum (2004, methodology): “Since the CAR’s are overlapping, we employ a heteroskedasticity-and-autocorrelation-consistent (HAC) estimate of the variance (Gallant (1987)), setting the number of lags equal to the number of overlapping months in the holding-period window (5, 11, or 47).8 As discussed earlier, the overreaction…”