opendf - an implementation of the dual fermion method for strongly correlated systems

The dual fermion method is a multiscale approach for solving lattice problems of interacting strongly correlated systems. In this paper, we present the \texttt{opendf} code, an open-source implementation of the dual fermion method applicable to fermionic single-orbital lattice models in dimensions $D=1,2,3$ and $4$. The method is built on a dynamical mean field starting point, which neglects all local correlations, and perturbatively adds spatial correlations. Our code is distributed as an open-source package under the GNU public license version 2.Comment: 7 pages, 6 figures, 28th Annual CSP Workshop proceeding

FARM MACHINERY INVESTMENT AND THE TAX REFORM ACT OF 1986

The Tax Reform Act of 1986 significantly changed incentives for investing. This analysis specifically examines how changes in marginal tax rates, depreciation schedules, and the investment tax credit altered the cost of capital and net investment in agriculture. A stochastic coefficients econometric methodology is used to estimate an investment function which is then used to simulate the effects of tax reform. Estimates indicated that relative to prior law, the Tax Reform Act will reduce the capital stock of farm machinery and equipment by nearly $4 billion.Agricultural Finance, Farm Management,

Experimental Results and Issues on Equalization for Nonlinear Memory Channel: Pre-Cursor Enhanced Ram-DFE Canceler

This thesis investigates the effects of the High Power Amplifier (HPA) and the filters over a satellite or telemetry channel. The Volterra series expression is presented for the nonlinear channel with memory, and the algorithm is based on the finite-state machine model. A RAM-based algorithm operating on the receiver side, Pre-cursor Enhanced RAM-FSE Canceler (PERC) is developed. A high order modulation scheme , 16-QAM is used for simulation, the results show that PERC provides an efficient and reliable method to transmit data on the bandlimited nonlinear channel. The contribution of PERC algorithm is that it includes both pre-cursors and post-cursors as the RAM address lines, and suggests a new way to make decision on the pre-addresses. Compared with the RAM-DFE structure that only includes post- addresses, the BER versus Eb/NO performance of PERC is substantially enhanced. Experiments are performed for PERC algorithms with different parameters on AWGN channels, and the results are compared and analyzed. The investigation of this thesis includes software simulation and hardware verification. Hardware is setup to collect actual TWT data. Simulation on both the software-generated data and the real-world data are performed. Practical limitations are considered for the hardware collected data. Simulation results verified the reliability of the PERC algorithm. This work was conducted at NMSU in the Center for Space Telemetering and Telecommunications Systems in the Klipsch School of Electrical and Computer Engineering Department

Semiparametric estimation exploiting covariate independence in two-phase randomized trials.

Recent results for case-control sampling suggest when the covariate distribution is constrained by gene-environment independence, semiparametric estimation exploiting such independence yields a great deal of efficiency gain. We consider the efficient estimation of the treatment-biomarker interaction in two-phase sampling nested within randomized clinical trials, incorporating the independence between a randomized treatment and the baseline markers. We develop a Newton-Raphson algorithm based on the profile likelihood to compute the semiparametric maximum likelihood estimate (SPMLE). Our algorithm accommodates both continuous phase-one outcomes and continuous phase-two biomarkers. The profile information matrix is computed explicitly via numerical differentiation. In certain situations where computing the SPMLE is slow, we propose a maximum estimated likelihood estimator (MELE), which is also capable of incorporating the covariate independence. This estimated likelihood approach uses a one-step empirical covariate distribution, thus is straightforward to maximize. It offers a closed-form variance estimate with limited increase in variance relative to the fully efficient SPMLE. Our results suggest exploiting the covariate independence in two-phase sampling increases the efficiency substantially, particularly for estimating treatment-biomarker interactions

AGRICULTURE IN AN ECOSYSTEMS FRAMEWORK

By broadening the definition of an ecosystem to include economic activities, can we better characterize the interactions and relationships among agricultural activities and important indicators of ecological system health? This paper addresses research approaches for assessing the role of agriculture in an ecosystems context. Environmental regulation and resource management policies have heightened the interest in understanding interactions among agricultural activities and the natural resource base, including the impacts of agriculture on environmental quality and the impacts on agriculture of ecosystem restoration efforts. What are the most meaningful indicators of environmental quality? Which agricultural practices and policies should be considered, along with which nonagricultural resource uses? Finally, does the evolving thinking about ecosystems permit us to link agricultural practices and policies more directly and meaningfully to conceptions of sustainability, of both natural and socioeconomic systems? This paper presents a brief synopsis of ecosystem management, drawing from several recent governmental initiatives. It then provides an overview of the economics of ecosystem management from the perspective of the role of agriculture; discusses two specific cases, the Pacific Northwest and South Florida; and concludes with a discussion of promising economic approaches, data needs, and caveats to those engaged in policy analysis involving ecosystem restoration.Environmental Economics and Policy,

When parties are not teams: party positions in single-member district and proportional representation systems

Theoretical analyses of party positions commonly assume that parties act as teams to maximize their legislative representation. This assumption runs counter to another line of theorizing in which individual legislators maximize their own chances of winning reelection. To resolve this tension, the paper presents a model of partyplatform choice that relaxes only the assumption that parties are teams in the classical two-party spatial model. Platforms are chosen by majority rule among all legislators within a party. Politicians seek to win their own seats in the legislature, but they must run under a common party label. In both single-member district and proportional representation systems, equilibrium platforms are shown to diverge substantially, with one party located near the 25th percentile of the voter distribution and the other near the 75th percentile, rather than converge to the median. The model also yields predictions concerning short-term economic shocks, incumbency advantages, and gerrymandering.Governmen

On Two-Stage Hypothesis Testing Procedures Via Asymptotically Independent Statistics

Kooperberg and LeBlanc (2008) proposed a two-stage testing procedure to screen for significant interactions in genome-wide association (GWA) studies by a soft threshold on marginal associations (MA), though its theoretical properties and generalization have not been elaborated. In this article, we discuss conditions that are required to achieve strong control of the Family-Wise Error Rate (FWER) by such procedures for low or high-dimensional hypothesis testing. We provide proof of asymptotic independence of marginal association statistics and interaction statistics in linear regression, logistic regression, and Cox proportional hazard models in a randomized clinical trial (RCT) with a rare event. In case-control studies nested within a RCT, a complementary criterion, namely deviation from baseline independence (DBI) in the case-control sample, is advocated as a screening tool for discovering significant interactions or main effects. Simulations and an application to a GWA study in Women’s Health Initiative (WHI) are presented to show utilities of the proposed two-stage testing procedures in pharmacogenetic studies