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sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the … all rectangles, or more generally, sparsely convex sets, and does not require any restrictions on the correlation among … functions depend nontrivially only on a small subset of their arguments, with rectangles being a special case. …
Persistent link: https://www.econbiz.de/10011525777
sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the … all rectangles, or more generally, sparsely convex sets, and does not require any restrictions on the correlation among … functions depend nontrivially only on a small subset of their arguments, with rectangles being a special case. …
Persistent link: https://www.econbiz.de/10011445703
sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the … all rectangles, or more generally, sparsely convex sets, and does not require any restrictions on the correlation among … functions depend nontrivially only on a small subset of their arguments, with rectangles being a special case. …
Persistent link: https://www.econbiz.de/10011594349
high-dimensional centered random vectors X1, . . . , Xn over the class of rectangles in the case when the covariance matrix …
Persistent link: https://www.econbiz.de/10012482915
We derive a central limit theorem for the maximum of a sum of high dimensional random vectors. More precisely, we establish condi- tions under which the distribution of the maximum is approximated by the maximum of a sum of the Gaussian random vectors with the same covariance matrices as the...
Persistent link: https://www.econbiz.de/10009692028
Persistent link: https://www.econbiz.de/10015357780
This chapter develops a novel bootstrap procedure to obtain robust bias-corrected confidence intervals in regression discontinuity (RD) designs. The procedure uses a wild bootstrap from a second-order local polynomial to estimate the bias of the local linear RD estimator; the bias is then...
Persistent link: https://www.econbiz.de/10015363285
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Persistent link: https://www.econbiz.de/10015426963
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