Rank-based estimation for all-pass time series models

An autoregressive-moving average model in which all roots of the autoregressive polynomial are reciprocals of roots of the moving average polynomial and vice versa is called an all-pass time series model. All-pass models are useful for identifying and modeling noncausal and noninvertible autoregressive-moving average processes. We establish asymptotic normality and consistency for rank-based estimators of all-pass model parameters. The estimators are obtained by minimizing the rank-based residual dispersion function given by Jaeckel [Ann. Math. Statist. 43 (1972) 1449--1458]. These estimators can have the same asymptotic efficiency as maximum likelihood estimators and are robust. The behavior of the estimators for finite samples is studied via simulation and rank estimation is used in the deconvolution of a simulated water gun seismogram.Comment: Published at http://dx.doi.org/10.1214/009053606000001316 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Searching for jet rotation in Class 0/I sources observed with GEMINI/GNIRS.

Original article can be found at: http://www.aanda.org/ Copyright The European Southern ObservatoryContext: In recent years, there has been a number of detections of gradients in the radial velocity profile across jets from young stars. The significance of these results is considerable. They may be interpreted as a signature of jet rotation about its symmetry axis, thereby representing the only existing observational indications supporting the theory that jets extract angular momentum from star-disk systems. However, the possibility that we are indeed observing jet rotation in pre-main sequence systems is undergoing active debate. Aims: To test the validity of a rotation argument, we must extend the survey to a larger sample, including younger sources. Methods: We present the latest results of a radial velocity analysis on jets from Class 0 and I sources, using high resolution data from the infrared spectrograph GNIRS on GEMINI South. We obtained infrared spectra of protostellar jets HH 34, HH 111-H, HH 212 NK1 and SK1. Results: The [Fe II] emission was unresolved in all cases and so Doppler shifts across the jet width could not be accessed. The H2 emission was resolved in all cases except HH 34. Doppler profiles across the molecular emission were obtained, and gradients in radial velocity of typically 3 km s-1 identified. Conclusions: Agreement with previous studies implies they may be interpreted as jet rotation, leading to toroidal velocity and angular momentum flux estimates of 1.5 km s-1 and 1 × 10-5 yr-1 AU km s-1 respectively. However, caution is needed. For example, emission is asymmetric across the jets from HH 212 suggesting a more complex interpretation is warranted. Furthermore, observations for HH 212 and HH 111-H are conducted far from the source implying external influences are more likely to confuse the intrinsic flow kinematics. These observations demonstrate the difficulty of conducting this study from the ground, and highlight the necessity for high angular resolution via adaptive optics or space-based facilities

The Rent-Price Ratio for the Aggregate Stock of Owner-Occupied Housing

We construct a time series of the rent-price ratio for the owner- occupied stock of housing, starting in 1960:1, by merging micro data from the last five Decennial Censuses of Housing with price indexes for house prices and rents.House Prices, Housing, Rents, CMHPI, Capitalization Rates

Housing flexibility effects on rotor stability

Preliminary rotordynamic evaluations are performed with a housing stiffness assumption that is typically determined only after the hardware is built. In addressing rotor stability, a rigid housing assumption was shown to predict an instability at a lower spin speed than a comparable flexible housing analysis. This rigid housing assumption therefore provides a conservative estimate of the stability threshold speed. A flexible housing appears to act as an energy absorber and dissipated some of the destabilizing force. The fact that a flexible housing is usually asymmetric and considerably heavier than the rotor was related to this apparent increase in rotor stability. Rigid housing analysis is proposed as a valuable screening criteria and may save time and money in construction of elaborate housing finite element models for linear stability analyses

Doppler lidar observations of sensible heat flux and intercomparisons with a ground-based energy balance station and WRF model output

This is an open access article - Copyright @ 2009 E. Schweizerbart'sche VerlagsbuchhandlungDuring the Convective and Orographically induced Precipitation Study (COPS), a scanning Doppler lidar was deployed at Achern, Baden-Wüttemberg, Germany from 13th June to 16th August 2007. Vertical velocity profiles ('rays') through the boundary layer were measured every 3 seconds with vertical profiles of horizontal wind velocity being derived from performing azimuth scans every 30 minutes. During Intense Observation Periods radiosondes were launched from the site. In this paper, a case study of convective boundary layer development on 15th July 2007 is investigated. Estimates of eddy dissipation rate are made from the vertically pointing lidar data and used as one input to the velocity-temperature co-variance equation to estimate sensible heat flux. The sensible heat flux values calculated from Doppler lidar data are compared with a surface based energy balance station and output from the Weather Research and Forecasting (WRF) model.Funding is obtained from NER

Evidence from scanning tunneling microscopy in support of a structural model for the InSb(001)-c(8×2) surface

In this letter we present evidence from scanning tunneling microscopy studies in support of a recently proposed structural model for the indium-terminated c(8×2) surface of InSb(001). This structural model, by Norris and co-workers, is based on a surface x-ray diffraction study [Surf. Sci. 409, 27 (1998)], and represents a significant departure from previously suggested models for the c(8×2) reconstruction on any (001) surface of the common III–V semiconductor materials. Although filled state images of the InSb(001)-c(8×2) surface have previously been published, empty states image of sufficient quality to extract any meaningful information have not previously been reported. The observations are in excellent agreement with the recently proposed model for this surface reconstruction

Determining the influence and effects of manufacturing variables on sulfur dioxide cells

A survey of the Li/SO2 manufacturing community was conducted to determine where variability exists in processing. The upper and lower limits of these processing variables might, by themselves or by interacting with other variables, influence safety, performance, and reliability. A number of important variables were identified and a comprehensive design experiment is being proposed to make the proper determinations

Estimating the Expected Value of Partial Perfect Information in Health Economic Evaluations using Integrated Nested Laplace Approximation

The Expected Value of Perfect Partial Information (EVPPI) is a decision-theoretic measure of the "cost" of parametric uncertainty in decision making used principally in health economic decision making. Despite this decision-theoretic grounding, the uptake of EVPPI calculations in practice has been slow. This is in part due to the prohibitive computational time required to estimate the EVPPI via Monte Carlo simulations. However, recent developments have demonstrated that the EVPPI can be estimated by non-parametric regression methods, which have significantly decreased the computation time required to approximate the EVPPI. Under certain circumstances, high-dimensional Gaussian Process regression is suggested, but this can still be prohibitively expensive. Applying fast computation methods developed in spatial statistics using Integrated Nested Laplace Approximations (INLA) and projecting from a high-dimensional into a low-dimensional input space allows us to decrease the computation time for fitting these high-dimensional Gaussian Processes, often substantially. We demonstrate that the EVPPI calculated using our method for Gaussian Process regression is in line with the standard Gaussian Process regression method and that despite the apparent methodological complexity of this new method, R functions are available in the package BCEA to implement it simply and efficiently