semiparametric estimation
Semiparametric estimation exploiting covariate independence in two-phase randomized trials.
... independence, semiparametric estimation exploiting such independence yields a great deal of efficiency ...efficient estimation of the treatment-biomarker interaction in two-phase sampling nested ...
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Essays on semiparametric estimation of Markov decision processes
... 00001t tif Essays on Semiparametric Estimation of Markov Decision Processes Sorawoot Srisuma Thesis submitted for the degree of Doctor of Philosophy in Economics at the London School of Economics and[.] ...
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Nonparametric and semiparametric estimation and testing
... the estimation of so-called 'Engle-curves’, ...regression estimation may be the only way to appropriately explain the relationship between the above ...
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Efficient semiparametric estimation of a partially linear quantile regression model
... regression estimation, the usual kinds of data-based band- width selection do not affect the first-order asymptotics of the estimators ~see, e+g+, Andrews, 1995!+ 7+ The condition that S~ x! is nonsingular at ...
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Semiparametric Estimation and Inference for Censored Regression Models.
... For the simplest Scenario 1 with homoscedastic error and covariate-independent censoring, all three methods give essentially unbiased estimation. The resampling procedure for the LBJ method works reasonably well. ...
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Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models
... Further, we contribute to the literature by putting forward two test statistics to test for pa- rameter constancy in our model. These model specification tests allow us to discriminate between a standard linear spatial ...
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Semiparametric Estimation of First Price Auction Models
... Though a fully nonparametric estimator has some desirable properties such as flexibility and robustness to misspecification, it has a number of drawbacks such as a slow consistency rate and the difficulty to consider a ...
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The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
... Recent methods for estimating sparse undirected graphs for real-valued data in high dimensional problems rely heavily on the assumption of normality. We show how to use a semiparametric Gaus- sian copula—or ...
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Long memory in time series: Semiparametric estimation and conditional heteroscedasticity
... 00001t tif Long M em ory in T im e Series Sem ip aram etric E stim a tio n and C on d ition al H e te ro sc e d a stic ity by M a r c H e n r y London School o f Economics and Political Science T hesi[.] ...
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Robustness, semiparametric estimation and goodness of fit of latent trait models
... 00001t tif R o b u stn ess, Sem iparam etric E stim a tio n and G ood n ess of F it o f L atent Trait M o d els P a n a g io ta T z a m o u r a n i L o n d o n S c h o o l o f E c o n o m ic s a n d P[.] ...
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Inequality and development: Evidence from semiparametric estimation with panel data
... Li, H., Squire, L., Zou, H.-F., 1998. Explaining international and intertemporal 16 variations in income inequality. Economic Journal 108, 26–43. 17 Lin, S.-C., Huang, H.-C., Weng, H.-W., 2006. A semiparametric ...
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Semiparametric estimation of a panel data proportional hazards model with fixed effects
... variance as compared to the uncensored counterpart. Therefore, it may be an interesting problem to develop a more efficient estimator than one proposed here. Furthermore, it may also be interesting to find the ...
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Semiparametric Estimation of Multivariate GARCH Models
... simple semiparametric estimator of the conditional variance-covari- ance and correlation matrix ...straightforward estimation also for the non-symultaneous case, ...
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Semiparametric estimation of diffusion models with applications in finance
... Observe th a t if 7To was known, we would be in a fully param etric framework and 6 would be the maximum-likelihood estim ator (MLE), which under regularity conditions would enjoy full efficiency. B ut since we have not ...
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Nonparametric and Semiparametric Models - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... or semiparametric estimation of those models is much more complicated and technical than most of what we aim to introduce in this ...these estimation problems are rather particular and the treatment ...
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Estimation of semiparametric econometric time series models with non linear or heteroscedastic disturbances
... Most of the theory about the NN-estimators has been developed in an i.i.d. environment. There are some results on k-NN estimators under dependence, i.e. by Collomb (1985) and Yakowitz (1987), but nothing so far as we ...
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nihms935418.pdf
... However, semiparametric estimation of the AFT model is highly challenging, even in the case of right-censored data (Prentice, 1978; Buckley and James, 1979; Tsiatis, 1990; Lai and Ying, 1991; Zeng and Lin, ...
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A semiparametric copula method for Cox models with covariate measurement error
... Table 2 shows the estimated effect of physical activity on breast cancer survival using the new semiparametric-copula estimators, compared to the naive Cox approach. The univariate analysis results were from a ...
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KIM_unc_0153D_13929.pdf
... Case-cohort study design is generally used to reduce cost in large cohort studies. When several diseases are of interest, several case-cohort studies are usually conducted using the same subcohort. When these case-cohort ...
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Identifying behaviour in a multiproduct oligopoly: Incumbents reaction to tariffs dismantling
... a semiparametric specification to simultaneously test for behaviour and estimate own and cross elasticities from the price equations, free of constraints imposed by functional form assumptions on the form of ...
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