14,421 research outputs found
RBF multiscale collocation for second order elliptic boundary value problems
In this paper, we discuss multiscale radial basis function collocation methods for solving elliptic partial differential equations on bounded domains. The approximate solution is constructed in a multi-level fashion, each level using compactly supported radial basis functions of smaller scale on an increasingly fine mesh. On each level, standard symmetric collocation is employed. A convergence theory is given, which builds on recent theoretical advances for multiscale approximation using compactly supported radial basis functions. We are able to show that the convergence is linear in the number of levels. We also discuss the condition numbers of the arising systems and the effect of simple, diagonal preconditioners, now proving rigorously previous numerical observations
The Matanuska-Susitna Borough Community Survey, 2006: A Sourcebook of Community Attitudes
The Matanuska-Susitna Borough Community Survey (Mat-Su Survey) was a cooperative effort on the part of Mat-Su College, the University of Alaska-Anchorage (UAA) and the Matanuska-Susitna Borough which asked Mat-Su Borough residents to evaluate the quality of Borough services, provide opinions about Borough decision-making, and sum up their perceptions about a range of issues relevant to the present and future of the Mat-Su community. The survey was distributed to every Borough household in the spring of 2006; a total of 2,600 were received, coded, and analyzed for the report. The Sourcebook provides detailed tabular results in six major areas: (1) evaluation of current borough services; (2) use of borough facilities; (3) life in Mat-Su neighborhoods; (4) local government access, policies, and practices; (5) higher education; and (6) respondent background information.Matanuska Susitna BoroughIntroduction /
SECTION 1 DETAILED BOROUGH-WIDE RESULTS /
Evaluation of Current Borough Services /
Use of Borough Facilities /
Life in Matanuska-Susitna Borough Neighborhoods /
Local Government: Access, Policies and Practices /
Higher Education /
Respondent Background Information /
SECTION 2: RESULTS FOR GEOGRAPHIC AREAS WITHIN THE BOROUGH /
Evaluation of Current Borough Services /
Use of Borough Facilities /
Life in Matanuska-Susitna Borough Neighborhoods /
Local Government: Access, Policies and Practices /
Higher Education /
Respondent Background Information /
APPENDIX A: Questionnair
Advanced space system analysis software. Technical, user, and programmer guide
The LASS computer program provides a tool for interactive preliminary and conceptual design of LSS. Eight program modules were developed, including four automated model geometry generators, an associated mass properties module, an appendage synthesizer module, an rf analysis module, and an orbital transfer analysis module. The existing rigid body controls analysis module was modified to permit analysis of effects of solar pressure on orbital performance. A description of each module, user instructions, and programmer information are included
Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs
Modern empirical work in Regression Discontinuity (RD) designs often employs
local polynomial estimation and inference with a mean square error (MSE)
optimal bandwidth choice. This bandwidth yields an MSE-optimal RD treatment
effect estimator, but is by construction invalid for inference. Robust bias
corrected (RBC) inference methods are valid when using the MSE-optimal
bandwidth, but we show they yield suboptimal confidence intervals in terms of
coverage error. We establish valid coverage error expansions for RBC confidence
interval estimators and use these results to propose new inference-optimal
bandwidth choices for forming these intervals. We find that the standard
MSE-optimal bandwidth for the RD point estimator is too large when the goal is
to construct RBC confidence intervals with the smallest coverage error. We
further optimize the constant terms behind the coverage error to derive new
optimal choices for the auxiliary bandwidth required for RBC inference. Our
expansions also establish that RBC inference yields higher-order refinements
(relative to traditional undersmoothing) in the context of RD designs. Our main
results cover sharp and sharp kink RD designs under conditional
heteroskedasticity, and we discuss extensions to fuzzy and other RD designs,
clustered sampling, and pre-intervention covariates adjustments. The
theoretical findings are illustrated with a Monte Carlo experiment and an
empirical application, and the main methodological results are available in
\texttt{R} and \texttt{Stata} packages
On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference
Nonparametric methods play a central role in modern empirical work. While
they provide inference procedures that are more robust to parametric
misspecification bias, they may be quite sensitive to tuning parameter choices.
We study the effects of bias correction on confidence interval coverage in the
context of kernel density and local polynomial regression estimation, and prove
that bias correction can be preferred to undersmoothing for minimizing coverage
error and increasing robustness to tuning parameter choice. This is achieved
using a novel, yet simple, Studentization, which leads to a new way of
constructing kernel-based bias-corrected confidence intervals. In addition, for
practical cases, we derive coverage error optimal bandwidths and discuss
easy-to-implement bandwidth selectors. For interior points, we show that the
MSE-optimal bandwidth for the original point estimator (before bias correction)
delivers the fastest coverage error decay rate after bias correction when
second-order (equivalent) kernels are employed, but is otherwise suboptimal
because it is too "large". Finally, for odd-degree local polynomial regression,
we show that, as with point estimation, coverage error adapts to boundary
points automatically when appropriate Studentization is used; however, the
MSE-optimal bandwidth for the original point estimator is suboptimal. All the
results are established using valid Edgeworth expansions and illustrated with
simulated data. Our findings have important consequences for empirical work as
they indicate that bias-corrected confidence intervals, coupled with
appropriate standard errors, have smaller coverage error and are less sensitive
to tuning parameter choices in practically relevant cases where additional
smoothness is available
Response of Fishes to Revetment Placement
Routine fish sampling with hoop nets was conducted monthly from April through December 1978 along natural and revetted riverbanks on the lower Mississippi River near Eudora, Arkansas, to monitor changes in fish populations affected by placement of new revetment for bank protection. Eighteen species of fish were collected with four species comprising over 75% of the total catch. During the months prior to revetment placement, freshwater drum, Aplodinotus grunniens, was the most abundant (32.7% of the catch) species collected. Following in abundance were the flathead catfish, Pylodictis olivaris, (9.8%), common carp, Cyprinus carpio, (7.8%), and blue catfish, Ictalurus furcatus, (3.3%). After revetment placement in August 1978, the freshwater drum was again the most abundant component, comprising 9.7% of the catch. Gizzard shad, Dorosoma cepedianum, flathead catfish, and blue catfish followed in abundance and comprised 8.9, 4.1, and 3.4% of the total catch, respectively. Catch per effort data indicated that fish were generally more abundant at natural bank stations than revetted bank stations but the difference was not significant. The study suggests that fish inhabiting natural riverbank habitat recover quite rapidly from bank perturbation caused by the placement of revetment
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