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-dimension, we propose a conditional variable screening test based on non-parametric regression using neural networks due to their … more generally a set of variables. Our test statistics are based on the estimated partial derivative of the regression … much predictors contribute additionally to the non-parametric regression after accounting for the latent factors. Our …
Persistent link: https://www.econbiz.de/10015053806
of a regression t - statistic in cases where the numerator is standard normal, but the denominator is √Q with Q an …
Persistent link: https://www.econbiz.de/10012800783
In this paper, we derive new, nearly optimal bounds for the Gaussian approximation to scaled averages of n independent high-dimensional centered random vectors X1, . . . , Xn over the class of rectangles in the case when the covariance matrix of the scaled average is non-degenerate. In the case...
Persistent link: https://www.econbiz.de/10012482915
This paper introduces Stata commands [R] npivreg and [R] npivregcv, which implement nonparametric instrumental variable (NPIV) estimation methods without and with a cross-validated choice of tuning parameters, respectively. Both commands are able to impose monotonicity of the estimated function....
Persistent link: https://www.econbiz.de/10011758353
. Examples of such parameters include individual regression coefficients, average treatment effects, average lifts, and demand or … leading cases of estimation and inference on the main parameter in a partially linear regression model and estimation and …
Persistent link: https://www.econbiz.de/10011538313
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This paper proposes a powerful alternative to the t-test of the null hypothesis that a coefficient in linear regression …. We propose a new maximal t-statistic that is formed from the regression of the outcome onto a maximally weighted linear …
Persistent link: https://www.econbiz.de/10014416040