40,969 research outputs found
Rate optimal multiple testing procedure in high-dimensional regression
Multiple testing and variable selection have gained much attention in
statistical theory and methodology research. They are dealing with the same
problem of identifying the important variables among many (Jin, 2012). However,
there is little overlap in the literature. Research on variable selection has
been focusing on selection consistency, i.e., both type I and type II errors
converging to zero. This is only possible when the signals are sufficiently
strong, contrary to many modern applications. For the regime where the signals
are both rare and weak, it is inevitable that a certain amount of false
discoveries will be allowed, as long as some error rate can be controlled. In
this paper, motivated by the research by Ji and Jin (2012) and Jin (2012) in
the rare/weak regime, we extend their UPS procedure for variable selection to
multiple testing. Under certain conditions, the new UPT procedure achieves the
fastest convergence rate of marginal false non-discovery rates, while
controlling the marginal false discovery rate at any designated level
asymptotically. Numerical results are provided to demonstrate the advantage of
the proposed method.Comment: 27 page
FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test
The maximum mean discrepancy (MMD) is a recently proposed test statistic for
two-sample test. Its quadratic time complexity, however, greatly hampers its
availability to large-scale applications. To accelerate the MMD calculation, in
this study we propose an efficient method called FastMMD. The core idea of
FastMMD is to equivalently transform the MMD with shift-invariant kernels into
the amplitude expectation of a linear combination of sinusoid components based
on Bochner's theorem and Fourier transform (Rahimi & Recht, 2007). Taking
advantage of sampling of Fourier transform, FastMMD decreases the time
complexity for MMD calculation from to , where and
are the size and dimension of the sample set, respectively. Here is the
number of basis functions for approximating kernels which determines the
approximation accuracy. For kernels that are spherically invariant, the
computation can be further accelerated to by using the Fastfood
technique (Le et al., 2013). The uniform convergence of our method has also
been theoretically proved in both unbiased and biased estimates. We have
further provided a geometric explanation for our method, namely ensemble of
circular discrepancy, which facilitates us to understand the insight of MMD,
and is hopeful to help arouse more extensive metrics for assessing two-sample
test. Experimental results substantiate that FastMMD is with similar accuracy
as exact MMD, while with faster computation speed and lower variance than the
existing MMD approximation methods
Conceptual development of a novel photovoltaic-thermoelectric system and preliminary economic analysis
© 2016 Elsevier Ltd Photovoltaic-thermoelectric (PV-TE) hybrid system is one typical electrical production based on the solar wide-band spectral absorption. However the PV-TE system appears to be economically unfeasible owing to the significantly higher cost and lower power output. In order to overcome this disadvantage, a novel PV-TE system based on the flat plate micro-channel heat pipe was proposed in this paper. The mathematic model was built and the performance under different ambient conditions was analyzed. In addition, the annual performance and the preliminary economic analysis of the new PV-TE system was also made to compare to the conventional PV system. The results showed that the new PV-TE has a higher electrical output and economic performance
- …