Nonparametric conditional distribution for the DEA-based
Nonparametric Inference Based on Conditional Moment Inequalities
... a nonparametric condi- tional quantile model with censoring and a nonparametric conditional treatment e¤ect ...the nonparametric smoothing parameter employed, but not much sensitivity to other ...
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Nonparametric Frontier Estimation: A Conditional Quantile-based Approach.
... two nonparametric methods based on envelopment techniques: the free disposal hull (FDH) and the data envelopment analysis ...The DEA estimator, which was initiated by Farrell (1957) and popularized ...
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Nonparametric Dynamic Conditional Beta
... joint distribution of excess stock returns and market returns are correctly specified then it follows that their contemporaneous pricing relationship is completely determined by the associated conditional ...
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Nonparametric estimation of some characteristics of the conditional distribution in single functional index model
... the conditional cumulative distribution function and that of the conditional density derivatives, and we give their pointwise almost complete convergence (with ...the conditional cumula- tive ...
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Nonparametric tests for conditional independence using conditional distributions
... of conditional distribution, however almost all the empirical works focus on causality in ...a nonparametric statistic to test the conditional independence and Granger non-causality between ...
31
Nonparametric tests for conditional independence using conditional distributions.
... the conditional mean, however the concept of causality is naturally defined in terms of conditional distribution; see Granger (1980) and Granger and Newbold ...in distribution has been less ...
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Nonparametric estimation and inference for conditional density based Granger causality measures.
... a nonparametric estimation and inference for conditional density based Granger causality mea- sures that quantify linear and nonlinear Granger ...measures based on a consistent ...
33
A nonparametric copula based test for conditional independence with applications to granger causality
... of conditional independence, see Florens and Mouchart (1982), Florens and Foug` ere (1996) and Chalak and White (2008), these tests can be deduced from the conditional independence ...
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A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality
... of conditional independence, see Florens and Mouchart (1982), Florens and Foug` ere (1996) and Chalak and White (2008), these tests can be deduced from the conditional independence ...
43
Conditional Ordering Using Nonparametric Expectiles
... 4 An application 4.1 The data set We focus on a data set that contains measurements on 2801 physicians in the Midi-Pyr´en´ees region of France during 1999, including most of the general prac- tice physicians in this ...
23
Adaptive Nonparametric Regression with Conditional Heteroskedasticity
... error distribution and is adaptive to the unknown error ...the conditional mean and variance functions jointly, we relax the symmetry assumption on the error density, which is very helpful for applications ...
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Nonparametric Inferences on Conditional Quantile Processes
... of conditional quantile functions or more generally as tests of how certain covariates affect the distribution of an outcome variable of ...to nonparametric inference prob- lems regarding ...
33
Nonparametric estimation of the conditional tail copula
... numerous nonparametric estimators of the Pickands dependence function have been introduced [5, 15, 32, 40] thanks to an interpretation of A in terms of exponential ...and nonparametric inference methods for ...
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Nonparametric Tests of Conditional Treatment Effects
... of nonparametric tests for treatment effects con- ditional on ...regarding conditional treatment effects, including (i) the null hypothesis of the conditional stochastic dominance between treatment ...
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Nonparametric estimation of the conditional mean residual life function based on censored data
... hazard based model that ...hazard based model is the estimate of ...average, based on the current cumulative observation and the individual explanatory ...
26
A note on nonparametric estimation of circular conditional densities
... circular, conditional mean and quantiles, when the explanatory variable is either linear or circular, has been recently studied by [2] and [3], ...for conditional density ...of conditional density ...
12
Conditional beta pricing models: A nonparametric approach
... flexible conditional beta pricing models in different ...estimates conditional covariances and conditional expected returns nonparametrically, and then obtains MPR by solving directly the system of ...
46
Nonparametric Tests for Conditional Symmetry in Dynamic Models.
... value based on the standard empirical ...of conditional symmetry around a parametric function in a time series ...testing conditional symmetry in econometric ...higher conditional moments of ...
31
Nonparametric estimation of conditional beta pricing models
... the conditional asset pricing model for two assets at each point in ...that conditional expected pricing errors from the conditional CAPM are ...is based on the idea that a simple regression ...
41
On the estimation of a monotone conditional variance in nonparametric regression
... the conditional variance is a function of the conditional mean, which depends monotonically on an explanatory ...monotone conditional expectation [see ...monotone conditional variance, which ...
25