作者：Sur, Pragya; Chen, Yuxin; Candes, Emmanuel J.
作者单位：Stanford University; Princeton University; Stanford University
摘要：Logistic regression is used thousands of times a day to fit data, predict future outcomes, and assess the statistical significance of explanatory variables. When used for the purpose of statistical inference, logistic models produce p-values for the regression coefficients by using an approximation to the distribution of the likelihood-ratio test (LRT). Indeed, Wilks' theorem asserts that whenever we have a fixed number p of variables, twice the log-likelihood ratio (LLR) 2 Lambda is distribut...
作者：Ben Arous, Gerard; Cabezas, Manuel; Fribergh, Alexander
作者单位：New York University; Pontificia Universidad Catolica de Chile; Universite de Montreal
摘要：We prove that, after suitable rescaling, the simple random walk on the trace of a large critical branching random walk in Zd converges to the Brownian motion on the integrated super-Brownian excursion when d>14.
