[PDF] Top 20 Observed Information in Semiparametric Models
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Observed Information in Semiparametric Models
... at observed data points) version of the ef®cient information ...some models, the special structure of the model leads to other estimators (Parner ... See full document
32
Semiparametric Mixed Models for Censored Longitudinal Data.
... the observed data and the current parameter estimates, and the M-step computes the updates of model parameters by maximizing the expected log-likelihood obtained from the E ... See full document
99
Semiparametric Bayesian inference in multiple equation models
... prior information about the smoothness of the nonparametric regression line was all that was required to ensure valid posterior ...prior information can be used to surmount the problem of insufficient ... See full document
28
Semiparametric Bayesian inference in multiple equation models
... In both the schooling and wage equations, we include the respondent’s Armed Forces Qualifying Test (AFQT) score which is standardized by age (denoted ABILITY), highest grade completed by the respondent’s mother (MOMED) ... See full document
29
Semiparametric Estimation of First Price Auction Models
... incomplete information in which asymmetric information among players (seller/buyer and bidders) is one of the key ...that observed bids are the equilibrium outcomes of the underlying auction model ... See full document
62
Semiparametric Estimation and Inference for Censored Regression Models.
... The semiparametric AFT model assumes that the random errors are i . i . d . and independent of the covariates. Most existing estimation methods rely on this assumption. However, in many applications, the random ... See full document
86
Estimating Semiparametric Panel Data Models by Marginal Integration
... the computational procedure for our estimator is noniterative, hence it is easy to imple- ment in practice and also fast enough for finite sample investigations using Monte Carlo simulations. The disadvantage of our ... See full document
37
Semiparametric estimation of diffusion models with applications in finance
... the observed ones as closely as ...have observed solutions to the PD E (bond and derivative prices) from which we wish to extract an estim ator of the one of th e coefficients driving th e ... See full document
189
Semiparametric Bayesian inference in smooth coefficient models
... is observed for at least five years throughout the sample ...is observed for approximately ten years of the panel, and for some individuals, we have as many ... See full document
33
Identification, estimation and efficiency of nonparametric and semiparametric models in microeconometrics
... separable models, where r (x, z) = Yl t =i @k (%k) + F (z) or its generalized version r ( x , z ) = # E j t = i Gk {%k) + ^ ( 2 ...of models Horowitz considers. However, m any econometric models ... See full document
211
Semiparametric prediction models for variables related with energy production
... the semiparametric model for half an hour ...external information slightly improves the prediction because the measure point for the meteorological variables is lo- cated at 80 m over ground level which is ... See full document
16
A semiparametric copula method for Cox models with covariate measurement error
... Gaussian kernel and Epanechnikov kernel, and then used the AIC for copula model selection. However, a model selection procedure based on AIC alone does not provide any information on the adequacy of the copula ... See full document
19
Testing for the absence of unobserved confounding in Semiparametric Bivariate Probit Models
... selection models address an issue which arises when observations are not from a random sample of the ...of observed and unobserved ...important observed characteristics from the sample of unselected ... See full document
28
Semiparametric Likelihood Ratio Inference
... parametric models this is the density of the ob- servations, while empirical likelihood theory uses the product Q P X i ...a semiparametric likelihood estimator is not necessarily discrete (although it ... See full document
39
Estimation in semiparametric models with missing data
... metric models with missing ...of models, whereas we aim in this paper at developing a general approach, applicable not only to regression models (with missing responses and/or covariates), but also ... See full document
25
Semiparametric Regression Models for Interacting Covariates.
... method was slightly higher with a maximum gain in power of 49%. When the correlation was low or nonexistent, the naive method had higher power, but the maximum gain was only 13%. When the extraneous SNPs were included ... See full document
84
Endogeneity in semiparametric binary response models
... parametric models of this kind the control function approach to the estimation of simultaneous equations models can be linked directly to conditional likelihood and in that setting it has been used ... See full document
51
On Semiparametric Exponential Family Graphical Models
... general semiparametric model and (2) it can be used to handle mixed data, which means that X may contain both continuous and discrete random ...graphical models, we allow the nodewise conditional ... See full document
59
Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models
... linear semiparametric spatial models recently proposed in the literature (Su & Jin, 2010; Su, 2012; Zhang, 2013; Sun, Hongjia, Zhang & Lu, 2014), its distinct feature is that it permits the spatial ... See full document
46
Endogeneity in nonparametric and semiparametric regression models
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