Cite
Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models.
MLA
Csaji, Balazs Csanad, et al. “Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models.” IEEE Transactions on Signal Processing, vol. 63, no. 1, Jan. 2015, pp. 169–81. EBSCOhost, https://doi.org/10.1109/TSP.2014.2369000.
APA
Csaji, B. C., Campi, M. C., & Weyer, E. (2015). Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models. IEEE Transactions on Signal Processing, 63(1), 169–181. https://doi.org/10.1109/TSP.2014.2369000
Chicago
Csaji, Balazs Csanad, Marco Claudio Campi, and Erik Weyer. 2015. “Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models.” IEEE Transactions on Signal Processing 63 (1): 169–81. doi:10.1109/TSP.2014.2369000.