Hermitian forms for affine Hecke algebras

We study star operations for Iwahori-Hecke algebras and invariant hermitian forms for finite dimensional modules over (graded) affine Hecke algebras with a view towards a unitarity algorithm.Comment: 29 pages, preliminary version. v2: the classification of star operations for the graded Hecke algebras and the construction of hermitian forms in the Iwahori case via Bernstein's projectives have been removed from this preprint and they will make the basis of a new pape

Star operations for affine Hecke algebras

In this paper, we consider the star operations for (graded) affine Hecke algebras which preserve certain natural filtrations. We show that, up to inner conjugation, there are only two such star operations for the graded Hecke algebra: the first, denoted $\star$, corresponds to the usual star operation from reductive $p$-adic groups, and the second, denoted $\bullet$ can be regarded as the analogue of the compact star operation of a real group considered by \cite{ALTV}. We explain how the star operation $\bullet$ appears naturally in the Iwahori-spherical setting of $p$-adic groups via the endomorphism algebras of Bernstein projectives. We also prove certain results about the signature of $\bullet$-invariant forms and, in particular, about $\bullet$-unitary simple modules.Comment: 27 pages; section 3 and parts of sections 2 and 5 were previously contained in the first version of the preprint arXiv:1312.331

Ladder representations of GL(n,Q_p)

In this paper, we recover certain known results about the ladder representations of GL(n, Q_p) defined and studied by Lapid, Minguez, and Tadic. We work in the equivalent setting of graded Hecke algebra modules. Using the Arakawa-Suzuki functor from category O to graded Hecke algebra modules, we show that the determinantal formula proved by Lapid-Minguez and Tadic is a direct consequence of the BGG resolution of finite dimensional simple gl(n)-modules. We make a connection between the semisimplicity of Hecke algebra modules, unitarity with respect to a certain hermitian form, and ladder representations.Comment: 14 page

Benchmarking Utility Clean Energy Deployment: 2016

Benchmarking Utility Clean Energy Deployment: 2016 provides a window into how the global transition toward clean energy is playing out in the U.S. electric power sector. Specifically, it reveals the extent to which 30 of the largest U.S. investor-owned electric utility holding companies are increasingly deploying clean energy resources to meet customer needs.Benchmarking these companies provides an opportunity for transparent reporting and analysis of important industry trends. It fills a knowledge gap by offering utilities, regulators, investors, policymakers and other stakeholders consistent and comparable information on which to base their decisions. And it provides perspective on which utilities are best positioned in a shifting policy landscape, including likely implementation of the U.S. EPA's Clean Power Plan aimed at reducing carbon pollution from power plants

The importance of distinct modeling strategies for gene and gene-specific treatment effects in hierarchical models for microarray data

When analyzing microarray data, hierarchical models are often used to share information across genes when estimating means and variances or identifying differential expression. Many methods utilize some form of the two-level hierarchical model structure suggested by Kendziorski et al. [Stat. Med. (2003) 22 3899-3914] in which the first level describes the distribution of latent mean expression levels among genes and among differentially expressed treatments within a gene. The second level describes the conditional distribution, given a latent mean, of repeated observations for a single gene and treatment. Many of these models, including those used in Kendziorski's et al. [Stat. Med. (2003) 22 3899-3914] EBarrays package, assume that expression level changes due to treatment effects have the same distribution as expression level changes from gene to gene. We present empirical evidence that this assumption is often inadequate and propose three-level hierarchical models as extensions to the two-level log-normal based EBarrays models to address this inadequacy. We demonstrate that use of our three-level models dramatically changes analysis results for a variety of microarray data sets and verify the validity and improved performance of our suggested method in a series of simulation studies. We also illustrate the importance of accounting for the uncertainty of gene-specific error variance estimates when using hierarchical models to identify differentially expressed genes.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS535 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org